MSHub: Medical Image Segmentation Hub with Pre-trained nnUNets

This project is the code for paper Adaptive Curriculum Query Strategy for Active Learning in Medical Image Classification published in MICCAI2024.

Scribbles or Points-based weakly-supervised learning for medical image segmentation, a strong baseline, and tutorial for research and application.

The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…

Awesome Active Domain Adaptation for Medical Image Analysis

[MICCAI2024] Rethinking Abdominal Organ Segmentation (RAOS) in the clinical scenario: A robustness evaluation benchmark with challenging cases

Related medical image dataset from OpenMedLab and others.

a pytorch version for SIFA, Unsupervised Bidirectional Cross-Modality Adaptation via Deeply Synergistic Image and Feature Alignment for Medical Image Segmentation

FPL+: Filtered Pseudo Label-based Unsupervised Cross-Modality Adaptation for 3D Medical Image Segmentation

[GreenJournal2023] Deep learning-based accurate delineation of primary gross tumor volume of nasopharyngeal carcinoma on heterogeneous magnetic resonance imaging: a large-scale and multi-center study

[MedIA2022]WORD: A large scale dataset, benchmark and clinical applicable study for abdominal organ segmentation from CT image

The first large protein language model trained follows structure instructions.

Maybe an easier nnUNet. I change the way to iter data during training leading an easier way to control the dataloader. And part of the codes are directly comes from nnUNet.

[MedIA2021]MIDeepSeg: Minimally Interactive Segmentation of Unseen Objects from Medical Images Using Deep Learning

This is the program for my LNQ2023 challenge to train the model and generate docker.

Semi-supervised Medical Image Segmentation through Dual-task Consistency

Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.

(TMI-2024) Source-Free Active Domain Adaptation (SFADA) for GTV Segmentation across Multiple Hospitals