{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Using TensorFlow backend.\n" ] } ], "source": [ "import os\n", "import sys\n", "import six\n", "import glob\n", "import math\n", "import pandas as pd\n", "import numpy as np\n", "from keras.utils import to_categorical\n", "import scipy.ndimage as nd\n", "from scipy.ndimage import zoom\n", "import random" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "import keras\n", "import tensorflow as tf\n", "from keras import Model\n", "from keras import backend as K\n", "from keras.regularizers import l2\n", "from keras.engine import Layer,InputSpec\n", "from keras.layers.merge import concatenate\n", "from keras.callbacks import TensorBoard,Callback\n", "from keras.layers.advanced_activations import LeakyReLU\n", "from keras.preprocessing.image import ImageDataGenerator\n", "from keras.layers.normalization import BatchNormalization\n", "from keras.callbacks import ModelCheckpoint, ReduceLROnPlateau\n", "from keras import initializers, regularizers, constraints,optimizers\n", "from keras.callbacks import ModelCheckpoint, LearningRateScheduler,TensorBoard\n", "from keras.layers import Add,Input,Conv3D,Convolution3D,Dropout,UpSampling3D,Concatenate,MaxPooling3D,\\\n", "GlobalAveragePooling3D,Dense,GlobalMaxPooling3D,Lambda,Activation,Reshape,Permute, PReLU, Deconvolution3D,Multiply,GlobalAveragePooling3D,Dense" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "from InstanceNorm import InstanceNormalization" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "num_blocks = 5\n", "# strides = [2,2,2,2,2]\n", "strides = [1,2,2,2,2]\n", "nodule_seg_strides = [1,2,2,2,2]\n", "# atrous_rates = [1,1,2,4,8]\n", "atrous_rates = [1,1,1,1,1]\n", "base_filters = 32\n", "norm_func = InstanceNormalization\n", "activation_func = LeakyReLU\n", "kernel_size = 3\n", "padding = 'same'\n", "dropout_rate = 0\n", "input_shape = (32,64,64,1)\n", "num_classes = 1" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "{\n", " \"training\": {\n", " \"train_file\": \"../files/train_files.json\",\n", " \"val_txt\": \"../files/val_files.json\",\n", " \"encoder\":\"NoduleSegEncoder_proxima\",\n", " \"encoder_file\":\"\",\n", " \"decoder_file\":\"\",\n", " \"decoder\":\"NoduleSegDecoder_proxima\",\n", " \"num_classes\": 1,\n", " \"voxel_size\":32,\n", " \"num_slice\":64,\n", " \"load_pre_trained\": false,\n", " \"pre_model_file\": \"\",\n", " \"base_path\":'/hdd/disk4/Segmentation/Weights',\n", " \"n_channels\": 1,\n", " \"early_stop\": 10,\n", " \"initial_learning_rate\": 5*1e-4,\n", " \"learning_rate_drop\": 0.5,\n", " \"train_batch_size\": 2,\n", " \"val_batch_size\": 2,\n", " \"normalizer\": [-1024.0, 400.0],\n", " \"n_epochs\": 25,\n", " \"shuffle\": true,\n", " \"aug\": true,\n", " \n", " }\n", "}" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "from ResNet import Resnet3DBuilder\n", "from VGGmodel import VGG\n", "from NoduleSegEncoder import NoduleSegEncoder_proxima\n" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "from CommonLayers import *\n", "# from NoduleSegDecoder import NoduleSegDecoder_proxima\n", "sys.path.append('../decoders/')\n", "from NoduleSegDecoder import NoduleSegDecoder_proxima" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "parameter_list = {\n", " 'num_blocks':num_blocks,\n", " 'strides':strides,\n", " 'atrous_rates':atrous_rates,\n", " 'base_filters':base_filters,\n", " 'norm_func':norm_func,\n", " 'activation_func':activation_func,\n", " 'kernel_size':kernel_size,\n", " 'padding':padding,\n", " 'dropout_rate':dropout_rate,\n", " 'num_classes':1,\n", " 'classification_layers':GlobalMaxPooling3D\n", "}" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "resnet_parameter_list = {\n", " 'base_filters':base_filters,\n", " 'norm_func':norm_func,\n", " 'activation_func':activation_func,\n", " 'kernel_size':kernel_size,\n", " 'padding':padding,\n", " 'dropout_rate':dropout_rate,\n", " 'num_classes':1,\n", " 'classification_layers':GlobalMaxPooling3D,\n", " 'init_kernel_size':1\n", "}" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "noduleseg_parameter_list = {\n", " 'num_blocks':num_blocks,\n", " 'strides':nodule_seg_strides,\n", " 'atrous_rates':[1 for _ in range(num_blocks)],\n", " 'base_filters':base_filters,\n", " 'norm_func':norm_func,\n", " 'activation_func':activation_func,\n", " 'kernel_size':kernel_size,\n", " 'padding':padding,\n", " 'dropout_rate':0.5,\n", " 'num_classes':1,\n", " 'classification_layers':GlobalMaxPooling3D\n", "}" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "result = NoduleSegEncoder_proxima(input_shape,**noduleseg_parameter_list)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "result1 = VGG(input_shape,**parameter_list)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "resnet_builder = Resnet3DBuilder(**resnet_parameter_list)\n", "result_res = resnet_builder.build_resnet_50(input_shape)" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "noduleseg_decoder_parameter_list = {\n", " 'kernel_initializer':'he_normal',\n", " 'kernel_regularizer':l2(1e-4),\n", " 'kernel_size':kernel_size,\n", " 'final_kernel_size':1,\n", " 'norm_func':norm_func,\n", " 'activation_func':activation_func,\n", " 'kernel_size':kernel_size,\n", " 'padding':padding,\n", " 'seg_num_class':1,\n", " 'merge_axis':-1,\n", " 'SEB_choice':True,\n", " 'ACR_choice':False,\n", " 'OCR_choice':False,\n", " 'deep_supervision':True,\n", " 'num_units':[3,3,3,3]\n", " \n", " \n", " \n", " \n", "}" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "model = NoduleSegDecoder_proxima(result,**noduleseg_decoder_parameter_list)" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "__________________________________________________________________________________________________\n", "Layer (type) Output Shape Param # Connected to \n", "==================================================================================================\n", "input_1 (InputLayer) (None, 32, 64, 64, 1 0 \n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock01_conv_01 (C (None, 32, 64, 64, 3 896 input_1[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock01_norm_01 (I (None, 32, 64, 64, 3 2 NoduleSegConvBlock01_conv_01[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock01_activation (None, 32, 64, 64, 3 0 NoduleSegConvBlock01_norm_01[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock01_conv_02 (C (None, 32, 64, 64, 3 27680 NoduleSegConvBlock01_activation_0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock01_norm_02 (I (None, 32, 64, 64, 3 2 NoduleSegConvBlock01_conv_02[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock01_activation (None, 32, 64, 64, 3 0 NoduleSegConvBlock01_norm_02[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock01_conv_03 (C (None, 32, 64, 64, 3 27680 NoduleSegConvBlock01_activation_0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock01_norm_03 (I (None, 32, 64, 64, 3 2 NoduleSegConvBlock01_conv_03[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock01_activation (None, 32, 64, 64, 3 0 NoduleSegConvBlock01_norm_03[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock01_add (Add) (None, 32, 64, 64, 3 0 NoduleSegConvBlock01_activation_0\n", " NoduleSegConvBlock01_activation_0\n", "__________________________________________________________________________________________________\n", "NoduleSegEncoderDropout01 (Drop (None, 32, 64, 64, 3 0 NoduleSegConvBlock01_add[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock02_conv_01 (C (None, 16, 32, 32, 6 55360 NoduleSegEncoderDropout01[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock02_norm_01 (I (None, 16, 32, 32, 6 2 NoduleSegConvBlock02_conv_01[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock02_activation (None, 16, 32, 32, 6 0 NoduleSegConvBlock02_norm_01[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock02_conv_02 (C (None, 16, 32, 32, 6 110656 NoduleSegConvBlock02_activation_0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock02_norm_02 (I (None, 16, 32, 32, 6 2 NoduleSegConvBlock02_conv_02[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock02_activation (None, 16, 32, 32, 6 0 NoduleSegConvBlock02_norm_02[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock02_conv_03 (C (None, 16, 32, 32, 6 110656 NoduleSegConvBlock02_activation_0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock02_norm_03 (I (None, 16, 32, 32, 6 2 NoduleSegConvBlock02_conv_03[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock02_activation (None, 16, 32, 32, 6 0 NoduleSegConvBlock02_norm_03[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock02_add (Add) (None, 16, 32, 32, 6 0 NoduleSegConvBlock02_activation_0\n", " NoduleSegConvBlock02_activation_0\n", "__________________________________________________________________________________________________\n", "NoduleSegEncoderDropout02 (Drop (None, 16, 32, 32, 6 0 NoduleSegConvBlock02_add[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock03_conv_01 (C (None, 8, 16, 16, 12 221312 NoduleSegEncoderDropout02[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock03_norm_01 (I (None, 8, 16, 16, 12 2 NoduleSegConvBlock03_conv_01[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock03_activation (None, 8, 16, 16, 12 0 NoduleSegConvBlock03_norm_01[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock03_conv_02 (C (None, 8, 16, 16, 12 442496 NoduleSegConvBlock03_activation_0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock03_norm_02 (I (None, 8, 16, 16, 12 2 NoduleSegConvBlock03_conv_02[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock03_activation (None, 8, 16, 16, 12 0 NoduleSegConvBlock03_norm_02[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock03_conv_03 (C (None, 8, 16, 16, 12 442496 NoduleSegConvBlock03_activation_0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock03_norm_03 (I (None, 8, 16, 16, 12 2 NoduleSegConvBlock03_conv_03[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock03_activation (None, 8, 16, 16, 12 0 NoduleSegConvBlock03_norm_03[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock03_add (Add) (None, 8, 16, 16, 12 0 NoduleSegConvBlock03_activation_0\n", " NoduleSegConvBlock03_activation_0\n", "__________________________________________________________________________________________________\n", "NoduleSegEncoderDropout03 (Drop (None, 8, 16, 16, 12 0 NoduleSegConvBlock03_add[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock04_conv_01 (C (None, 4, 8, 8, 256) 884992 NoduleSegEncoderDropout03[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock04_norm_01 (I (None, 4, 8, 8, 256) 2 NoduleSegConvBlock04_conv_01[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock04_activation (None, 4, 8, 8, 256) 0 NoduleSegConvBlock04_norm_01[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock04_conv_02 (C (None, 4, 8, 8, 256) 1769728 NoduleSegConvBlock04_activation_0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock04_norm_02 (I (None, 4, 8, 8, 256) 2 NoduleSegConvBlock04_conv_02[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock04_activation (None, 4, 8, 8, 256) 0 NoduleSegConvBlock04_norm_02[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock04_conv_03 (C (None, 4, 8, 8, 256) 1769728 NoduleSegConvBlock04_activation_0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock04_norm_03 (I (None, 4, 8, 8, 256) 2 NoduleSegConvBlock04_conv_03[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock04_activation (None, 4, 8, 8, 256) 0 NoduleSegConvBlock04_norm_03[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock04_add (Add) (None, 4, 8, 8, 256) 0 NoduleSegConvBlock04_activation_0\n", " NoduleSegConvBlock04_activation_0\n", "__________________________________________________________________________________________________\n", "NoduleSegEncoderDropout04 (Drop (None, 4, 8, 8, 256) 0 NoduleSegConvBlock04_add[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock05_conv_01 (C (None, 2, 4, 4, 512) 3539456 NoduleSegEncoderDropout04[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock05_norm_01 (I (None, 2, 4, 4, 512) 2 NoduleSegConvBlock05_conv_01[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock05_activation (None, 2, 4, 4, 512) 0 NoduleSegConvBlock05_norm_01[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock05_conv_02 (C (None, 2, 4, 4, 512) 7078400 NoduleSegConvBlock05_activation_0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock05_norm_02 (I (None, 2, 4, 4, 512) 2 NoduleSegConvBlock05_conv_02[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock05_activation (None, 2, 4, 4, 512) 0 NoduleSegConvBlock05_norm_02[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock05_conv_03 (C (None, 2, 4, 4, 512) 7078400 NoduleSegConvBlock05_activation_0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock05_norm_03 (I (None, 2, 4, 4, 512) 2 NoduleSegConvBlock05_conv_03[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock05_activation (None, 2, 4, 4, 512) 0 NoduleSegConvBlock05_norm_03[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegConvBlock05_add (Add) (None, 2, 4, 4, 512) 0 NoduleSegConvBlock05_activation_0\n", " NoduleSegConvBlock05_activation_0\n", "__________________________________________________________________________________________________\n", "NoduleSegEncoderDropout05 (Drop (None, 2, 4, 4, 512) 0 NoduleSegConvBlock05_add[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_SEB_pr (None, 2, 4, 4, 512) 0 NoduleSegEncoderDropout05[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_SEB_co (None, 2, 4, 4, 256) 3539200 NoduleSegDecoder_Block01_SEB_preU\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_SEB_no (None, 2, 4, 4, 256) 2 NoduleSegDecoder_Block01_SEB_conv\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_upsamp (None, 4, 8, 8, 512) 0 NoduleSegEncoderDropout05[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_SEB_ac (None, 2, 4, 4, 256) 0 NoduleSegDecoder_Block01_SEB_norm\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_conv_0 (None, 4, 8, 8, 256) 3539200 NoduleSegDecoder_Block01_upsample\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_SEB_up (None, 4, 8, 8, 256) 0 NoduleSegDecoder_Block01_SEB_acti\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_norm_0 (None, 4, 8, 8, 256) 2 NoduleSegDecoder_Block01_conv_01[\n", "__________________________________________________________________________________________________\n", "multiply_4 (Multiply) (None, 4, 8, 8, 256) 0 NoduleSegDecoder_Block01_SEB_upsa\n", " NoduleSegEncoderDropout04[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_activa (None, 4, 8, 8, 256) 0 NoduleSegDecoder_Block01_norm_01[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_Concat (None, 4, 8, 8, 512) 0 multiply_4[0][0] \n", " NoduleSegDecoder_Block01_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_conv_0 (None, 4, 8, 8, 256) 3539200 NoduleSegDecoder_Block01_Concaten\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_norm_0 (None, 4, 8, 8, 256) 2 NoduleSegDecoder_Block01_conv_02[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_activa (None, 4, 8, 8, 256) 0 NoduleSegDecoder_Block01_norm_02[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_SEB_pr (None, 4, 8, 8, 512) 0 NoduleSegEncoderDropout05[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_SEB_pr (None, 4, 8, 8, 256) 0 NoduleSegEncoderDropout04[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_conv_0 (None, 4, 8, 8, 256) 1769728 NoduleSegDecoder_Block01_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_SEB_co (None, 4, 8, 8, 768) 0 NoduleSegDecoder_Block02_SEB_preU\n", " NoduleSegDecoder_Block02_SEB_preU\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_norm_0 (None, 4, 8, 8, 256) 2 NoduleSegDecoder_Block01_conv_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_SEB_co (None, 4, 8, 8, 128) 2654336 NoduleSegDecoder_Block02_SEB_conc\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_activa (None, 4, 8, 8, 256) 0 NoduleSegDecoder_Block01_norm_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_SEB_no (None, 4, 8, 8, 128) 2 NoduleSegDecoder_Block02_SEB_conv\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_upsamp (None, 8, 16, 16, 25 0 NoduleSegDecoder_Block01_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_SEB_ac (None, 4, 8, 8, 128) 0 NoduleSegDecoder_Block02_SEB_norm\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_conv_0 (None, 8, 16, 16, 12 884864 NoduleSegDecoder_Block02_upsample\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_SEB_up (None, 8, 16, 16, 12 0 NoduleSegDecoder_Block02_SEB_acti\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_norm_0 (None, 8, 16, 16, 12 2 NoduleSegDecoder_Block02_conv_01[\n", "__________________________________________________________________________________________________\n", "multiply_5 (Multiply) (None, 8, 16, 16, 12 0 NoduleSegDecoder_Block02_SEB_upsa\n", " NoduleSegEncoderDropout03[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_activa (None, 8, 16, 16, 12 0 NoduleSegDecoder_Block02_norm_01[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_Concat (None, 8, 16, 16, 25 0 multiply_5[0][0] \n", " NoduleSegDecoder_Block02_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_conv_0 (None, 8, 16, 16, 12 884864 NoduleSegDecoder_Block02_Concaten\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_norm_0 (None, 8, 16, 16, 12 2 NoduleSegDecoder_Block02_conv_02[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_activa (None, 8, 16, 16, 12 0 NoduleSegDecoder_Block02_norm_02[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_conv_0 (None, 8, 16, 16, 12 442496 NoduleSegDecoder_Block02_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_SEB_pr (None, 8, 16, 16, 51 0 NoduleSegEncoderDropout05[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_SEB_pr (None, 8, 16, 16, 25 0 NoduleSegEncoderDropout04[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_SEB_pr (None, 8, 16, 16, 12 0 NoduleSegEncoderDropout03[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_norm_0 (None, 8, 16, 16, 12 2 NoduleSegDecoder_Block02_conv_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_SEB_co (None, 8, 16, 16, 89 0 NoduleSegDecoder_Block03_SEB_preU\n", " NoduleSegDecoder_Block03_SEB_preU\n", " NoduleSegDecoder_Block03_SEB_preU\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_activa (None, 8, 16, 16, 12 0 NoduleSegDecoder_Block02_norm_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_SEB_co (None, 8, 16, 16, 64 1548352 NoduleSegDecoder_Block03_SEB_conc\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_SEB_no (None, 8, 16, 16, 64 2 NoduleSegDecoder_Block03_SEB_conv\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_upsamp (None, 16, 32, 32, 1 0 NoduleSegDecoder_Block02_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_SEB_ac (None, 8, 16, 16, 64 0 NoduleSegDecoder_Block03_SEB_norm\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_conv_0 (None, 16, 32, 32, 6 221248 NoduleSegDecoder_Block03_upsample\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_SEB_up (None, 16, 32, 32, 6 0 NoduleSegDecoder_Block03_SEB_acti\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_norm_0 (None, 16, 32, 32, 6 2 NoduleSegDecoder_Block03_conv_01[\n", "__________________________________________________________________________________________________\n", "multiply_6 (Multiply) (None, 16, 32, 32, 6 0 NoduleSegDecoder_Block03_SEB_upsa\n", " NoduleSegEncoderDropout02[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_activa (None, 16, 32, 32, 6 0 NoduleSegDecoder_Block03_norm_01[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_Concat (None, 16, 32, 32, 1 0 multiply_6[0][0] \n", " NoduleSegDecoder_Block03_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_conv_0 (None, 16, 32, 32, 6 221248 NoduleSegDecoder_Block03_Concaten\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_norm_0 (None, 16, 32, 32, 6 2 NoduleSegDecoder_Block03_conv_02[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_activa (None, 16, 32, 32, 6 0 NoduleSegDecoder_Block03_norm_02[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_conv_0 (None, 16, 32, 32, 6 110656 NoduleSegDecoder_Block03_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_norm_0 (None, 16, 32, 32, 6 2 NoduleSegDecoder_Block03_conv_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_activa (None, 16, 32, 32, 6 0 NoduleSegDecoder_Block03_norm_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_upsamp (None, 32, 64, 64, 6 0 NoduleSegDecoder_Block03_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_conv_0 (None, 32, 64, 64, 3 55328 NoduleSegDecoder_Block04_upsample\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_norm_0 (None, 32, 64, 64, 3 2 NoduleSegDecoder_Block04_conv_01[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_activa (None, 32, 64, 64, 3 0 NoduleSegDecoder_Block04_norm_01[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_Concat (None, 32, 64, 64, 6 0 NoduleSegEncoderDropout01[0][0] \n", " NoduleSegDecoder_Block04_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_conv_0 (None, 32, 64, 64, 3 55328 NoduleSegDecoder_Block04_Concaten\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_norm_0 (None, 32, 64, 64, 3 2 NoduleSegDecoder_Block04_conv_02[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_activa (None, 32, 64, 64, 3 0 NoduleSegDecoder_Block04_norm_02[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_conv_0 (None, 32, 64, 64, 3 27680 NoduleSegDecoder_Block04_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_norm_0 (None, 32, 64, 64, 3 2 NoduleSegDecoder_Block04_conv_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_activa (None, 32, 64, 64, 3 0 NoduleSegDecoder_Block04_norm_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 8, 16, 16, 8) 27656 NoduleSegDecoder_Block02_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 16, 32, 32, 8 13832 NoduleSegDecoder_Block03_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 32, 64, 64, 8 6920 NoduleSegDecoder_Block04_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 8, 16, 16, 8) 2 NoduleSegDeepCombineBlock_block01\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 16, 32, 32, 8 2 NoduleSegDeepCombineBlock_block02\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 32, 64, 64, 8 2 NoduleSegDeepCombineBlock_block03\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 8, 16, 16, 8) 0 NoduleSegDeepCombineBlock_block01\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 16, 32, 32, 8 0 NoduleSegDeepCombineBlock_block02\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 32, 64, 64, 8 0 NoduleSegDeepCombineBlock_block03\n", "__________________________________________________________________________________________________\n", "deep_supervision_upsample_01 (U (None, 32, 64, 64, 8 0 NoduleSegDeepCombineBlock_block01\n", "__________________________________________________________________________________________________\n", "deep_supervision_upsample_02 (U (None, 32, 64, 64, 8 0 NoduleSegDeepCombineBlock_block02\n", "__________________________________________________________________________________________________\n", "deep_supervision_upsample_03 (U (None, 32, 64, 64, 8 0 NoduleSegDeepCombineBlock_block03\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_DeepSupervisio (None, 32, 64, 64, 1 9 deep_supervision_upsample_01[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_DeepSupervisio (None, 32, 64, 64, 1 9 deep_supervision_upsample_02[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_DeepSupervisio (None, 32, 64, 64, 1 9 deep_supervision_upsample_03[0][0\n", "==================================================================================================\n", "Total params: 43,102,165\n", "Trainable params: 43,102,165\n", "Non-trainable params: 0\n", "__________________________________________________________________________________________________\n" ] } ], "source": [ "model.summary()" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "model1 = NoduleSegDecoder_proxima(result1,**noduleseg_decoder_parameter_list)" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "__________________________________________________________________________________________________\n", "Layer (type) Output Shape Param # Connected to \n", "==================================================================================================\n", "input_2 (InputLayer) (None, 32, 64, 64, 1 0 \n", "__________________________________________________________________________________________________\n", "VGG_block01_conv_01 (Conv3D) (None, 32, 64, 64, 3 896 input_2[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block01_norm_01 (InstanceNo (None, 32, 64, 64, 3 2 VGG_block01_conv_01[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block01_activation_01 (Leak (None, 32, 64, 64, 3 0 VGG_block01_norm_01[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block01_conv_02 (Conv3D) (None, 32, 64, 64, 3 27680 VGG_block01_activation_01[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block01_norm_02 (InstanceNo (None, 32, 64, 64, 3 2 VGG_block01_conv_02[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block01_activation_02 (Leak (None, 32, 64, 64, 3 0 VGG_block01_norm_02[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block02_conv_01 (Conv3D) (None, 32, 64, 64, 6 55360 VGG_block01_activation_02[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block02_norm_01 (InstanceNo (None, 32, 64, 64, 6 2 VGG_block02_conv_01[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block02_activation_01 (Leak (None, 32, 64, 64, 6 0 VGG_block02_norm_01[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block02_conv_02 (Conv3D) (None, 32, 64, 64, 6 110656 VGG_block02_activation_01[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block02_norm_02 (InstanceNo (None, 32, 64, 64, 6 2 VGG_block02_conv_02[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block02_activation_02 (Leak (None, 32, 64, 64, 6 0 VGG_block02_norm_02[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block02_pool (MaxPooling3D) (None, 16, 32, 32, 6 0 VGG_block02_activation_02[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block03_conv_01 (Conv3D) (None, 16, 32, 32, 1 221312 VGG_block02_pool[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block03_norm_01 (InstanceNo (None, 16, 32, 32, 1 2 VGG_block03_conv_01[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block03_activation_01 (Leak (None, 16, 32, 32, 1 0 VGG_block03_norm_01[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block03_conv_02 (Conv3D) (None, 16, 32, 32, 1 442496 VGG_block03_activation_01[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block03_norm_02 (InstanceNo (None, 16, 32, 32, 1 2 VGG_block03_conv_02[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block03_activation_02 (Leak (None, 16, 32, 32, 1 0 VGG_block03_norm_02[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block03_conv_03 (Conv3D) (None, 16, 32, 32, 1 442496 VGG_block03_activation_02[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block03_norm_03 (InstanceNo (None, 16, 32, 32, 1 2 VGG_block03_conv_03[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block03_activation_03 (Leak (None, 16, 32, 32, 1 0 VGG_block03_norm_03[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block03_pool (MaxPooling3D) (None, 8, 16, 16, 12 0 VGG_block03_activation_03[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block04_conv_01 (Conv3D) (None, 8, 16, 16, 25 884992 VGG_block03_pool[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block04_norm_01 (InstanceNo (None, 8, 16, 16, 25 2 VGG_block04_conv_01[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block04_activation_01 (Leak (None, 8, 16, 16, 25 0 VGG_block04_norm_01[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block04_conv_02 (Conv3D) (None, 8, 16, 16, 25 1769728 VGG_block04_activation_01[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block04_norm_02 (InstanceNo (None, 8, 16, 16, 25 2 VGG_block04_conv_02[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block04_activation_02 (Leak (None, 8, 16, 16, 25 0 VGG_block04_norm_02[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block04_conv_03 (Conv3D) (None, 8, 16, 16, 25 1769728 VGG_block04_activation_02[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block04_norm_03 (InstanceNo (None, 8, 16, 16, 25 2 VGG_block04_conv_03[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block04_activation_03 (Leak (None, 8, 16, 16, 25 0 VGG_block04_norm_03[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block04_pool (MaxPooling3D) (None, 4, 8, 8, 256) 0 VGG_block04_activation_03[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block05_conv_01 (Conv3D) (None, 4, 8, 8, 512) 3539456 VGG_block04_pool[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block05_norm_01 (InstanceNo (None, 4, 8, 8, 512) 2 VGG_block05_conv_01[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block05_activation_01 (Leak (None, 4, 8, 8, 512) 0 VGG_block05_norm_01[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block05_conv_02 (Conv3D) (None, 4, 8, 8, 512) 7078400 VGG_block05_activation_01[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block05_norm_02 (InstanceNo (None, 4, 8, 8, 512) 2 VGG_block05_conv_02[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block05_activation_02 (Leak (None, 4, 8, 8, 512) 0 VGG_block05_norm_02[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block05_conv_03 (Conv3D) (None, 4, 8, 8, 512) 7078400 VGG_block05_activation_02[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block05_norm_03 (InstanceNo (None, 4, 8, 8, 512) 2 VGG_block05_conv_03[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block05_activation_03 (Leak (None, 4, 8, 8, 512) 0 VGG_block05_norm_03[0][0] \n", "__________________________________________________________________________________________________\n", "VGG_block05_pool (MaxPooling3D) (None, 2, 4, 4, 512) 0 VGG_block05_activation_03[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_SEB_pr (None, 2, 4, 4, 512) 0 VGG_block05_pool[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_SEB_co (None, 2, 4, 4, 256) 3539200 NoduleSegDecoder_Block01_SEB_preU\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_SEB_no (None, 2, 4, 4, 256) 2 NoduleSegDecoder_Block01_SEB_conv\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_upsamp (None, 4, 8, 8, 512) 0 VGG_block05_pool[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_SEB_ac (None, 2, 4, 4, 256) 0 NoduleSegDecoder_Block01_SEB_norm\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_conv_0 (None, 4, 8, 8, 256) 3539200 NoduleSegDecoder_Block01_upsample\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_SEB_up (None, 4, 8, 8, 256) 0 NoduleSegDecoder_Block01_SEB_acti\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_norm_0 (None, 4, 8, 8, 256) 2 NoduleSegDecoder_Block01_conv_01[\n", "__________________________________________________________________________________________________\n", "multiply_7 (Multiply) (None, 4, 8, 8, 256) 0 NoduleSegDecoder_Block01_SEB_upsa\n", " VGG_block04_pool[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_activa (None, 4, 8, 8, 256) 0 NoduleSegDecoder_Block01_norm_01[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_Concat (None, 4, 8, 8, 512) 0 multiply_7[0][0] \n", " NoduleSegDecoder_Block01_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_conv_0 (None, 4, 8, 8, 256) 3539200 NoduleSegDecoder_Block01_Concaten\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_norm_0 (None, 4, 8, 8, 256) 2 NoduleSegDecoder_Block01_conv_02[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_activa (None, 4, 8, 8, 256) 0 NoduleSegDecoder_Block01_norm_02[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_SEB_pr (None, 4, 8, 8, 512) 0 VGG_block05_pool[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_SEB_pr (None, 4, 8, 8, 256) 0 VGG_block04_pool[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_conv_0 (None, 4, 8, 8, 256) 1769728 NoduleSegDecoder_Block01_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_SEB_co (None, 4, 8, 8, 768) 0 NoduleSegDecoder_Block02_SEB_preU\n", " NoduleSegDecoder_Block02_SEB_preU\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_norm_0 (None, 4, 8, 8, 256) 2 NoduleSegDecoder_Block01_conv_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_SEB_co (None, 4, 8, 8, 128) 2654336 NoduleSegDecoder_Block02_SEB_conc\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_activa (None, 4, 8, 8, 256) 0 NoduleSegDecoder_Block01_norm_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_SEB_no (None, 4, 8, 8, 128) 2 NoduleSegDecoder_Block02_SEB_conv\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_upsamp (None, 8, 16, 16, 25 0 NoduleSegDecoder_Block01_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_SEB_ac (None, 4, 8, 8, 128) 0 NoduleSegDecoder_Block02_SEB_norm\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_conv_0 (None, 8, 16, 16, 12 884864 NoduleSegDecoder_Block02_upsample\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_SEB_up (None, 8, 16, 16, 12 0 NoduleSegDecoder_Block02_SEB_acti\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_norm_0 (None, 8, 16, 16, 12 2 NoduleSegDecoder_Block02_conv_01[\n", "__________________________________________________________________________________________________\n", "multiply_8 (Multiply) (None, 8, 16, 16, 12 0 NoduleSegDecoder_Block02_SEB_upsa\n", " VGG_block03_pool[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_activa (None, 8, 16, 16, 12 0 NoduleSegDecoder_Block02_norm_01[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_Concat (None, 8, 16, 16, 25 0 multiply_8[0][0] \n", " NoduleSegDecoder_Block02_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_conv_0 (None, 8, 16, 16, 12 884864 NoduleSegDecoder_Block02_Concaten\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_norm_0 (None, 8, 16, 16, 12 2 NoduleSegDecoder_Block02_conv_02[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_activa (None, 8, 16, 16, 12 0 NoduleSegDecoder_Block02_norm_02[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_conv_0 (None, 8, 16, 16, 12 442496 NoduleSegDecoder_Block02_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_SEB_pr (None, 8, 16, 16, 51 0 VGG_block05_pool[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_SEB_pr (None, 8, 16, 16, 25 0 VGG_block04_pool[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_SEB_pr (None, 8, 16, 16, 12 0 VGG_block03_pool[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_norm_0 (None, 8, 16, 16, 12 2 NoduleSegDecoder_Block02_conv_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_SEB_co (None, 8, 16, 16, 89 0 NoduleSegDecoder_Block03_SEB_preU\n", " NoduleSegDecoder_Block03_SEB_preU\n", " NoduleSegDecoder_Block03_SEB_preU\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_activa (None, 8, 16, 16, 12 0 NoduleSegDecoder_Block02_norm_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_SEB_co (None, 8, 16, 16, 64 1548352 NoduleSegDecoder_Block03_SEB_conc\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_SEB_no (None, 8, 16, 16, 64 2 NoduleSegDecoder_Block03_SEB_conv\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_upsamp (None, 16, 32, 32, 1 0 NoduleSegDecoder_Block02_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_SEB_ac (None, 8, 16, 16, 64 0 NoduleSegDecoder_Block03_SEB_norm\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_conv_0 (None, 16, 32, 32, 6 221248 NoduleSegDecoder_Block03_upsample\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_SEB_up (None, 16, 32, 32, 6 0 NoduleSegDecoder_Block03_SEB_acti\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_norm_0 (None, 16, 32, 32, 6 2 NoduleSegDecoder_Block03_conv_01[\n", "__________________________________________________________________________________________________\n", "multiply_9 (Multiply) (None, 16, 32, 32, 6 0 NoduleSegDecoder_Block03_SEB_upsa\n", " VGG_block02_pool[0][0] \n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_activa (None, 16, 32, 32, 6 0 NoduleSegDecoder_Block03_norm_01[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_Concat (None, 16, 32, 32, 1 0 multiply_9[0][0] \n", " NoduleSegDecoder_Block03_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_conv_0 (None, 16, 32, 32, 6 221248 NoduleSegDecoder_Block03_Concaten\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_norm_0 (None, 16, 32, 32, 6 2 NoduleSegDecoder_Block03_conv_02[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_activa (None, 16, 32, 32, 6 0 NoduleSegDecoder_Block03_norm_02[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_conv_0 (None, 16, 32, 32, 6 110656 NoduleSegDecoder_Block03_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_norm_0 (None, 16, 32, 32, 6 2 NoduleSegDecoder_Block03_conv_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_activa (None, 16, 32, 32, 6 0 NoduleSegDecoder_Block03_norm_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_upsamp (None, 32, 64, 64, 6 0 NoduleSegDecoder_Block03_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_conv_0 (None, 32, 64, 64, 3 55328 NoduleSegDecoder_Block04_upsample\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_norm_0 (None, 32, 64, 64, 3 2 NoduleSegDecoder_Block04_conv_01[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_activa (None, 32, 64, 64, 3 0 NoduleSegDecoder_Block04_norm_01[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_Concat (None, 32, 64, 64, 6 0 VGG_block01_activation_02[0][0] \n", " NoduleSegDecoder_Block04_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_conv_0 (None, 32, 64, 64, 3 55328 NoduleSegDecoder_Block04_Concaten\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_norm_0 (None, 32, 64, 64, 3 2 NoduleSegDecoder_Block04_conv_02[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_activa (None, 32, 64, 64, 3 0 NoduleSegDecoder_Block04_norm_02[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_conv_0 (None, 32, 64, 64, 3 27680 NoduleSegDecoder_Block04_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_norm_0 (None, 32, 64, 64, 3 2 NoduleSegDecoder_Block04_conv_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_activa (None, 32, 64, 64, 3 0 NoduleSegDecoder_Block04_norm_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 8, 16, 16, 8) 27656 NoduleSegDecoder_Block02_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 16, 32, 32, 8 13832 NoduleSegDecoder_Block03_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 32, 64, 64, 8 6920 NoduleSegDecoder_Block04_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 8, 16, 16, 8) 2 NoduleSegDeepCombineBlock_block01\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 16, 32, 32, 8 2 NoduleSegDeepCombineBlock_block02\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 32, 64, 64, 8 2 NoduleSegDeepCombineBlock_block03\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 8, 16, 16, 8) 0 NoduleSegDeepCombineBlock_block01\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 16, 32, 32, 8 0 NoduleSegDeepCombineBlock_block02\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 32, 64, 64, 8 0 NoduleSegDeepCombineBlock_block03\n", "__________________________________________________________________________________________________\n", "deep_supervision_upsample_01 (U (None, 32, 64, 64, 8 0 NoduleSegDeepCombineBlock_block01\n", "__________________________________________________________________________________________________\n", "deep_supervision_upsample_02 (U (None, 32, 64, 64, 8 0 NoduleSegDeepCombineBlock_block02\n", "__________________________________________________________________________________________________\n", "deep_supervision_upsample_03 (U (None, 32, 64, 64, 8 0 NoduleSegDeepCombineBlock_block03\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_DeepSupervisio (None, 32, 64, 64, 1 9 deep_supervision_upsample_01[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_DeepSupervisio (None, 32, 64, 64, 1 9 deep_supervision_upsample_02[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_DeepSupervisio (None, 32, 64, 64, 1 9 deep_supervision_upsample_03[0][0\n", "==================================================================================================\n", "Total params: 42,963,825\n", "Trainable params: 42,963,825\n", "Non-trainable params: 0\n", "__________________________________________________________________________________________________\n" ] } ], "source": [ "model1.summary()" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": [ "model2 = NoduleSegDecoder_proxima(result_res,**noduleseg_decoder_parameter_list)" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "__________________________________________________________________________________________________\n", "Layer (type) Output Shape Param # Connected to \n", "==================================================================================================\n", "input_3 (InputLayer) (None, 32, 64, 64, 1 0 \n", "__________________________________________________________________________________________________\n", "ResNet_InitBlock_conv_01 (Conv3 (None, 32, 64, 64, 3 64 input_3[0][0] \n", "__________________________________________________________________________________________________\n", "ResNet_InitBlock_norm_01 (Insta (None, 32, 64, 64, 3 2 ResNet_InitBlock_conv_01[0][0] \n", "__________________________________________________________________________________________________\n", "ResNet_InitBlock_activation_01 (None, 32, 64, 64, 3 0 ResNet_InitBlock_norm_01[0][0] \n", "__________________________________________________________________________________________________\n", "ResNet_InitBlock_pool (MaxPooli (None, 16, 32, 32, 3 0 ResNet_InitBlock_activation_01[0]\n", "__________________________________________________________________________________________________\n", "ResNet_BottleNeckBlock01_1v1_co (None, 16, 32, 32, 6 2112 ResNet_InitBlock_pool[0][0] \n", "__________________________________________________________________________________________________\n", "ResNet_BottleNeckBlock01_1v1_no (None, 16, 32, 32, 6 2 ResNet_BottleNeckBlock01_1v1_conv\n", "__________________________________________________________________________________________________\n", "ResNet_BottleNeckBlock01_1v1_ac (None, 16, 32, 32, 6 0 ResNet_BottleNeckBlock01_1v1_norm\n", "__________________________________________________________________________________________________\n", "ResNet_BottleNeckBlock01_3v3__c (None, 16, 32, 32, 2 442624 ResNet_BottleNeckBlock01_1v1_acti\n", 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"__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_activa (None, 4.0, 8.0, 8.0 0 NoduleSegDecoder_Block01_norm_02[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_SEB_pr (None, 4.0, 8.0, 8.0 0 ResNet_BottleNeckBlock04_layer03_\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_SEB_pr (None, 4.0, 8.0, 8.0 0 ResNet_BottleNeckBlock03_layer06_\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_conv_0 (None, 4.0, 8.0, 8.0 1769728 NoduleSegDecoder_Block01_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_SEB_co (None, 4.0, 8.0, 8.0 0 NoduleSegDecoder_Block02_SEB_preU\n", " NoduleSegDecoder_Block02_SEB_preU\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_norm_0 (None, 4.0, 8.0, 8.0 2 NoduleSegDecoder_Block01_conv_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_SEB_co (None, 4.0, 8.0, 8.0 2654336 NoduleSegDecoder_Block02_SEB_conc\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block01_activa (None, 4.0, 8.0, 8.0 0 NoduleSegDecoder_Block01_norm_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_SEB_no (None, 4.0, 8.0, 8.0 2 NoduleSegDecoder_Block02_SEB_conv\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_upsamp (None, 8.0, 16.0, 16 0 NoduleSegDecoder_Block01_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_SEB_ac (None, 4.0, 8.0, 8.0 0 NoduleSegDecoder_Block02_SEB_norm\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_conv_0 (None, 8.0, 16.0, 16 884864 NoduleSegDecoder_Block02_upsample\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_SEB_up (None, 8.0, 16.0, 16 0 NoduleSegDecoder_Block02_SEB_acti\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_norm_0 (None, 8.0, 16.0, 16 2 NoduleSegDecoder_Block02_conv_01[\n", "__________________________________________________________________________________________________\n", "multiply_11 (Multiply) (None, 8.0, 16.0, 16 0 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"__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_norm_0 (None, 8.0, 16.0, 16 2 NoduleSegDecoder_Block02_conv_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_SEB_co (None, 8.0, 16.0, 16 0 NoduleSegDecoder_Block03_SEB_preU\n", " NoduleSegDecoder_Block03_SEB_preU\n", " NoduleSegDecoder_Block03_SEB_preU\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block02_activa (None, 8.0, 16.0, 16 0 NoduleSegDecoder_Block02_norm_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_SEB_co (None, 8.0, 16.0, 16 1548352 NoduleSegDecoder_Block03_SEB_conc\n", "__________________________________________________________________________________________________\n", 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"NoduleSegDecoder_Block03_norm_0 (None, 16.0, 32.0, 3 2 NoduleSegDecoder_Block03_conv_01[\n", "__________________________________________________________________________________________________\n", "multiply_12 (Multiply) (None, 16.0, 32.0, 3 0 NoduleSegDecoder_Block03_SEB_upsa\n", " ResNet_BottleNeckBlock01_layer03_\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_activa (None, 16.0, 32.0, 3 0 NoduleSegDecoder_Block03_norm_01[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_Concat (None, 16.0, 32.0, 3 0 multiply_12[0][0] \n", " NoduleSegDecoder_Block03_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_conv_0 (None, 16.0, 32.0, 3 221248 NoduleSegDecoder_Block03_Concaten\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_norm_0 (None, 16.0, 32.0, 3 2 NoduleSegDecoder_Block03_conv_02[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_activa (None, 16.0, 32.0, 3 0 NoduleSegDecoder_Block03_norm_02[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_conv_0 (None, 16.0, 32.0, 3 110656 NoduleSegDecoder_Block03_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_norm_0 (None, 16.0, 32.0, 3 2 NoduleSegDecoder_Block03_conv_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block03_activa (None, 16.0, 32.0, 3 0 NoduleSegDecoder_Block03_norm_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_upsamp (None, 32.0, 64.0, 6 0 NoduleSegDecoder_Block03_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_conv_0 (None, 32.0, 64.0, 6 55328 NoduleSegDecoder_Block04_upsample\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_norm_0 (None, 32.0, 64.0, 6 2 NoduleSegDecoder_Block04_conv_01[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_activa (None, 32.0, 64.0, 6 0 NoduleSegDecoder_Block04_norm_01[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_Concat (None, 32, 64, 64, 6 0 ResNet_InitBlock_activation_01[0]\n", " 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NoduleSegDecoder_Block04_conv_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_Block04_activa (None, 32, 64, 64, 3 0 NoduleSegDecoder_Block04_norm_03[\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 8.0, 16.0, 16 27656 NoduleSegDecoder_Block02_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 16.0, 32.0, 3 13832 NoduleSegDecoder_Block03_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 32, 64, 64, 8 6920 NoduleSegDecoder_Block04_activati\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 8.0, 16.0, 16 2 NoduleSegDeepCombineBlock_block01\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 16.0, 32.0, 3 2 NoduleSegDeepCombineBlock_block02\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 32, 64, 64, 8 2 NoduleSegDeepCombineBlock_block03\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 8.0, 16.0, 16 0 NoduleSegDeepCombineBlock_block01\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 16.0, 32.0, 3 0 NoduleSegDeepCombineBlock_block02\n", "__________________________________________________________________________________________________\n", "NoduleSegDeepCombineBlock_block (None, 32, 64, 64, 8 0 NoduleSegDeepCombineBlock_block03\n", "__________________________________________________________________________________________________\n", "deep_supervision_upsample_01 (U (None, 32.0, 64.0, 6 0 NoduleSegDeepCombineBlock_block01\n", "__________________________________________________________________________________________________\n", "deep_supervision_upsample_02 (U (None, 32.0, 64.0, 6 0 NoduleSegDeepCombineBlock_block02\n", "__________________________________________________________________________________________________\n", "deep_supervision_upsample_03 (U (None, 32, 64, 64, 8 0 NoduleSegDeepCombineBlock_block03\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_DeepSupervisio (None, 32.0, 64.0, 6 9 deep_supervision_upsample_01[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_DeepSupervisio (None, 32.0, 64.0, 6 9 deep_supervision_upsample_02[0][0\n", "__________________________________________________________________________________________________\n", "NoduleSegDecoder_DeepSupervisio (None, 32, 64, 64, 1 9 deep_supervision_upsample_03[0][0\n", "==================================================================================================\n", "Total params: 296,963,481\n", "Trainable params: 296,963,481\n", "Non-trainable params: 0\n", "__________________________________________________________________________________________________\n" ] } ], "source": [ "model2.summary()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": 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