Readers for medical imaging datasets

cardiac segmentation with 3d slicer

Sourcecode Compilation (medical related)

Code for automated brain tumor segmentation from MRI scans using CNNs with attention mechanisms, deep supervision, and Swin-Transformers. Based on my Master's dissertation project at Brunel University, it features 3 deep learning models, showcasing integration of advanced techniques in medical image analysis.

A simple modular U-Net library for medical image segmentation.

Abdominal Bleeding Detection using U-Net and CaraNet

Classifying Pneumonia images and normal lung images using RESNET50 and Customized CNN models.

Modular PyTorch U-Net model

Self-Supervised Learning with Swin UNETR for Segmentation of Organs at Risk and Tumor in PET/CT Images

[BSPC] The official code for "MHorUNet: High-order spatial interaction UNet for skin lesion segmentation".

Unofficial PyTorch implementation of SA-UNet

Unofficial PyTorch implementation of Mobile-PolypNet

monai_wholeBody_ct_segmentation

CIA block to Improve ViT's Attention Mechanism for Medical Image Segmentation

A comprehensive review of techniques to address the missing-modality problem for medical images

Public repository for "A deep learning toolkit for visualization and interpretation of segmented medical images"

Code implementation of our paper "Exploring Domain-specific Contrastive Learning with Consistency Regularization for Semi-supervised Medical Image Segmentation "

Performing Binary classification and Tensorflow Advanced Segmentation on lung X-Rays to detect if the individual is affected by pneumonia or not.

Modified MobileNet-ShuffleNet-GhostNet Network for Lightweight Retinal Vessel Segmentation

1st place solution for MICCAI challenge CrossMoDA 2023 (unsupervised domain adaptation for medical images)