amobiny/3D_Image_Segmentation

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Created over 6 years ago
Updated about 6 years ago

amobiny/3D_Image_Segmentation

amobiny

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3D implementation of some of the most famous networks used for segmentation

Fast_CapsNet

Official implementation of the Fast Capsule Network

Self-Supervised_Jigsaw_Puzzle

implementation of the paper "Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles" in TensorFlow and Keras

3D_ResNet_Tensorflow_Tensorboard

The object-oriented implementation of the Residual Network proposed in "Deep Residual Learning for Image Recognition" modified to be used for 3D images

Capsule_Network_Tensorflow

Capsule Network implementation in Tensorflow

CT_Semantic_Segmentation

Contains codes for algorithms used to delineate organs from CT images for thoracic patients in radiation treatment planning

Deep_Capsule_Network

Implementation of Deep Capsule Network using Convolutional Dynamic Routing

Recurrent_Attention_Model

Tensorflow implementation of RAM and DRAM networks

DECAPS_for_COVID19

Official implementation of the Detailed-oriented Capsule Network for detecting COVID-19 from CT scans

AlexNet-Tensorflow-Tensorboard

Implementation of AlexNet (CNN designed by Alex Krizhevsky) in Tensorflow+Tensorboard

Deep_CapsNet

Implementation of Capsule Networks with Dynamic Routing with several layers, introducing Convolutional Capsule connections

Apoptosis_Project

This repository contains codes of the methods used in the apoptosis project

3D-AlexNet-Tensorflow-Tensorboard

Implementation of AlexNet for 3D images in Tensorflow

hide_and_seek

Multi-Attention Multi-Task model for Fine-grained classification of common diseases in chest radiographs

python_interview_practice

NTM_tensorflow

BNN_Skin_Lesion

Bayesian Neural Network for Uncertainty Estimation in Skin Lesion Classification

chest_xray

HULA project on chest x-ray dataset

glomerulus_classification

AlexNet-for-Multi-task-Classification

This code is prepared for the Chest-Xray data classification task where each single image includes several conditions.