fitushar/3d-guidedgradcam-for-medical-imaging

This Repo containes the implemnetation of generating Guided-GradCAM for 3D medical Imaging using Nifti file in tensorflow 2.0. Different input files can be used in that case need to edit the input to the Guided-gradCAM model.

3D-GuidedGradCAM-for-Medical-Imaging

This Repo containes the implemnetation of generating Guided-GradCAM for 3D medical Imaging using Nifti file in tensorflow 2.0. Different input files can be used in that case need to edit the input to the Guided-gradCAM model.

Files:

   i) guided_Gradcam3D.py         |--> Generate Guided-GradCAM , input and output nifti data
  ii) Guided_GradCAM_3D_config.py |--> Configuration file for the Guided-GradCAM, Modify based on your need
 iii) Resnet_3D.py                |--> Network architecture
  iv) deploy_config.py               |--> Configuration file for the Network, Modify based on your need
   v) loss_funnction_And_matrics.py  |--> Loss functions for CNN

How to run

To run and generate Guided-GardCAM all is to need to configure the Guided_GradCAM_3D_config.py and deploy_config.py based on your requiremnet.

deploy_config.py-

CNN configuration Change based on your Network or complete replace by your CNN

import tensorflow as tf
import math
from loss_funnction_And_matrics import*
###---Number-of-GPU
NUM_OF_GPU=1
DISTRIIBUTED_STRATEGY_GPUS=["gpu:0","gpu:1","gpu:2"]
##Network Configuration
NUMBER_OF_CLASSES=5
INPUT_PATCH_SIZE=(224,160,160, 1)
TRAIN_NUM_RES_UNIT=3
TRAIN_NUM_FILTERS=(16, 32, 64, 128)
TRAIN_STRIDES=((1, 1, 1), (2, 2, 2), (2, 2, 2), (2, 2, 2))
TRAIN_CLASSIFY_ACTICATION=tf.nn.relu6
TRAIN_KERNAL_INITIALIZER=tf.keras.initializers.VarianceScaling(distribution='uniform')
TRAIN_CLASSIFY_LEARNING_RATE =1e-4
TRAIN_CLASSIFY_LOSS=Weighted_BCTL
OPTIMIZER=tf.keras.optimizers.Adam(lr=TRAIN_CLASSIFY_LEARNING_RATE,epsilon=1e-5)
TRAIN_CLASSIFY_METRICS=tf.keras.metrics.AUC()

Guided_GradCAM_3D_config.py

Input Configuration for the Guided-GradCAM

MODEL_WEIGHT="Path/of/Model/Weight/XXX.h5"
CLASS_INDEX=1 # Index of the class for which you want to see the Guided-gradcam
INPUT_PATCH_SIZE_SLICE_NUMBER=64 # Input patch slice you want to feed at a time
LAYER_NAME='conv3d_18' # Name of the layer from where you want to get the Guided-GradCAM
NIFTI_PATH="imput/niftidata/path/XXX.nii.gz"
SAVE_PATH="/Output/niftydata/path/ML_Guided_GradCaN_XXXX.nii.gz"

Sample Guided-GardCAM