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3d-augmentation-techniques

Chechink the performance of different augmentation techniques on the BraTS 2020 data.

3d-medical-imaging-preprocessing-all-you-need

This Repo Will contain the Preprocessing Code for 3D Medical Imaging

3dbraingen

Official Pytorch Implementation of "Generation of 3D Brain MRI Using Auto-Encoding Generative Adversarial Network" (accepted by MICCAI 2019)

3dstylegan

3D StyleGAN2 for Medical Images

altas-of-pelvis-segmentation-and-trajectory-planning

An open-source pelvis atlas is constructed to provide pelvis CT segmentations, statistical shape models, and surgical screw trajectories

awesome-fairness-in-ai

A curated list of awesome Fairness in AI resources

chatdoctor

convertisseur

Dicom to NIfTI

ctpelvic1k

Resources of the paper “Deep Learning to Segment Pelvic Bones: Large-scale CT Datasets and Baseline Models”.

data-augmentation-and-quality-evaluation

data-augmentation-review

List of useful data augmentation resources. You will find here some not common techniques, libraries, links to github repos, papers and others.

deep-learning-with-r-notebooks

R notebooks for the code samples of the book "Deep Learning with R"

dicom2nifti

fracnet

[eBioMedicine] Deep-learning-assisted detection and segmentation of rib fractures from CT scans: Development and validation of FracNet

generativemodels

MONAI Generative Models makes it easy to train, evaluate, and deploy generative models and related applications

ha-gan

Official PyTorch implementation for HA-GAN, a memory efficient 3D GAN, accepted to IEEE J-BHI

image-classification-pytorch

Learning and Building Convolutional Neural Networks using PyTorch

landmark-detection

Automatic tool for landmark localisation in 3D medical images

machinelearningnotebooks

Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft

medical-data

medical-detection3d-toolkit

Landmark and object detection engine for 3D medical images

medicalnet

Many studies have shown that the performance on deep learning is significantly affected by volume of training data. The MedicalNet project provides a series of 3D-ResNet pre-trained models and relative code.

miscnn

A framework for Medical Image Segmentation with Convolutional Neural Networks and Deep Learning

mlwithpytorch

Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch

nifti2dicom

Convert 3D NIfTI images (and other formats supported by ITK) to DICOM 2D series

pytorch-dl

This Repository contains notebook for learning pytorch and implementing deep learning model for both Computer Vision and Natural Language Processing

resampling

scanavagenerationtoolkit

A Semi-Supervised Data Augmentation Approach using 3D Graphical Engines (ECCVW2018)

shape_descriptors

Code for our MIDL 2021 submission

totalsegmentator

Tool for robust segmentation of 104 important anatomical structures in CT images