[ICLR 2024 oral; top 1.2%] Supervised Pre-Trained 3D Models for Medical Image Analysis (9,262 CT volumes + 25 annotated classes)
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Updated
Oct 1, 2026 - Python
[ICLR 2024 oral; top 1.2%] Supervised Pre-Trained 3D Models for Medical Image Analysis (9,262 CT volumes + 25 annotated classes)
MOOSE (Multi-organ objective segmentation) a data-centric AI solution that generates multilabel organ segmentations to facilitate systemic TB whole-person research.The pipeline is based on nn-UNet and has the capability to segment 120 unique tissue classes from a whole-body 18F-FDG PET/CT image.
3D Slicer extension for fully-automatic segmentation of CT and CBCT dental volumes.
Segmentation deep learning ALgorithm based on MONai toolbox: single and multi-label segmentation software developed by QIMP team-Vienna.
[CVPR 2025] nnWNet: Rethinking the Use of Transformers in Biomedical Image Segmentation and Calling for a Unified Evaluation Benchmark
3D Slicer nnUNet integration to streamline usage for nnUNet based AI extensions.
MIST: A simple and scalable end-to-end framework for 3D medical imaging segmentation.
cardiAc ultrasound Segmentation & Color-dopplEr dealiasiNg Toolbox (ASCENT)
LION: Lesion Segmentation. Simplified.
LightMIS: Ultra-Lightweight Medical Image Segmentation Without a Stage-Wise Decoder
Fully automated 3D perivascular space (PVS) segmentation tool for T1w and T2w brain MRI.
Playing with SimpleITK and nnU-Net to process data from the CHAOS challenge on Google Colab.
nnUNet benchmarks for The University of California San Francisco Brain Metastases Stereotactic Radiosurgery (UCSF-BMSR) dataset.
Official repository for "Pre- to Post-Contrast Breast MRI Synthesis for Enhanced Tumour Segmentation"
Automated cyst segmentation and counting pipeline for polycystic kidney disease µCT scans, using nnUNet and distance-transform peak detection with genetic algorithm parameter optimization.
Bi-temporal CTP–DWI tissue phenotyping for acute ischemic stroke (IEEE BHI 2026)
This is a repository hosting all models detailed in the article Brain tumour segmentation with incomplete imaging data.
Efficient Deep Learning-based Forward Solvers for Brain Tumor Growth Models
nnUNet benchmarks for The University of California San Francisco Adult Longitudinal Post-Treatment Diffuse Glioma (UCSF-ALPTDG) dataset.
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