All Projects → fitushar → 3D-GuidedGradCAM-for-Medical-Imaging

fitushar / 3D-GuidedGradCAM-for-Medical-Imaging

Licence: other
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.

Programming Languages

python
139335 projects - #7 most used programming language

Projects that are alternatives of or similar to 3D-GuidedGradCAM-for-Medical-Imaging

cnn-visualization-keras-tf2
Filter visualization, Feature map visualization, Guided Backprop, GradCAM, Guided-GradCAM, Deep Dream
Stars: ✭ 21 (-65%)
Mutual labels:  guided-grad-cam, cnn-visualization
Pytorch Cnn Visualizations
Pytorch implementation of convolutional neural network visualization techniques
Stars: ✭ 6,167 (+10178.33%)
Mutual labels:  guided-grad-cam, cnn-visualization
CARLA
CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
Stars: ✭ 166 (+176.67%)
Mutual labels:  explainable-ai, tensorflow2
gans-2.0
Generative Adversarial Networks in TensorFlow 2.0
Stars: ✭ 76 (+26.67%)
Mutual labels:  tensorflow-examples, tensorflow2
food-vision-mobile-tensorflowjs
Food Vision project for mobile devices using TensorFlowJS
Stars: ✭ 19 (-68.33%)
Mutual labels:  tensorflow-examples, tensorflow2
dicomifier
A medical image converter
Stars: ✭ 22 (-63.33%)
Mutual labels:  medical-imaging, nifti
GradCAM and GuidedGradCAM tf2
Implementation of GradCAM & Guided GradCAM with Tensorflow 2.x
Stars: ✭ 16 (-73.33%)
Mutual labels:  guided-grad-cam, tensorflow2
TF2-GAN
🐳 GAN implemented as Tensorflow 2.X
Stars: ✭ 61 (+1.67%)
Mutual labels:  tensorflow-examples, tensorflow2
Awesome-Tensorflow2
基于Tensorflow2开发的优秀扩展包及项目
Stars: ✭ 45 (-25%)
Mutual labels:  tensorflow-examples, tensorflow2
Eat tensorflow2 in 30 days
Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋
Stars: ✭ 9,166 (+15176.67%)
Mutual labels:  tensorflow-examples, tensorflow2
Medicaldetectiontoolkit
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
Stars: ✭ 917 (+1428.33%)
Mutual labels:  medical-imaging, 3d-models
few-shot-segmentation
PyTorch implementation of 'Squeeze and Excite' Guided Few Shot Segmentation of Volumetric Scans
Stars: ✭ 78 (+30%)
Mutual labels:  medical-imaging
tensorflow-maml
TensorFlow 2.0 implementation of MAML.
Stars: ✭ 79 (+31.67%)
Mutual labels:  tensorflow2
checkmate
Training neural networks in TensorFlow 2.0 with 5x less memory
Stars: ✭ 116 (+93.33%)
Mutual labels:  tensorflow2
Deep-Learning-liver-segmentation
Application of Deep Learning to the segmentation of medical images
Stars: ✭ 39 (-35%)
Mutual labels:  medical-imaging
direct
Deep learning framework for MRI reconstruction
Stars: ✭ 161 (+168.33%)
Mutual labels:  medical-imaging
manning tf2 in action
The official code repository for "TensorFlow in Action" by Manning.
Stars: ✭ 61 (+1.67%)
Mutual labels:  tensorflow2
time-series-annotator
Time series annotation library.
Stars: ✭ 52 (-13.33%)
Mutual labels:  medical-imaging
tf-examples
TensorFlow examples
Stars: ✭ 23 (-61.67%)
Mutual labels:  tensorflow-examples
TensorFlow-Binary-Image-Classification-using-CNN-s
Binary Image Classification in TensorFlow
Stars: ✭ 26 (-56.67%)
Mutual labels:  tensorflow-examples

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

SAMPLE Guided-GradCAM1 SAMPLE Guided-GradCAM2 SAMPLE Guided-GradCAM3

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].