Nnunet Python Packages

medh5

Self-describing HDF5 container for one medical imaging sample and all of its ground truth: multi-timepoint, multi-modal images with segmentation, detection, classification and registration annotations, provenance and integrity.

lionz

LION: Lesion Segmentation. Simplified.

mist-medical

MIST: A simple and scalable end-to-end framework for 3D medical imaging segmentation.

dlicv

A repository that allows users to apply the DLICV method to their brain imaging data.

lyroi

nnU-Net-based Lymphoma Total Metabolic Tumor Volume Segmentation

paddle-nnunet

nnUNet paddlepaddle version

segauge

Geometrically-correct, DICOM-native evaluation metrics for medical image segmentation in Python: Dice, IoU, HD95, ASSD, Normalized Surface Dice, per-lesion detection F1, with bootstrap confidence intervals and subgroup/fairness slicing.