MIC-DKFZ
Division of Medical Image Computing, German Cancer Research Center (DKFZ)
Heidelberg, Germany
Pinned Repositories
basic_unet_example
An example project of how to use a U-Net for segmentation on medical images with PyTorch.
batchgenerators
A framework for data augmentation for 2D and 3D image classification and segmentation
HD-BET
MRI brain extraction tool
medicaldetectiontoolkit
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
MedNeXt
[MICCAI 2023] MedNeXt is a fully ConvNeXt architecture for 3D medical image segmentation.
nnDetection
nnDetection is a self-configuring framework for 3D (volumetric) medical object detection which can be applied to new data sets without manual intervention. It includes guides for 12 data sets that were used to develop and evaluate the performance of the proposed method.
nnInteractive
nnInteractive is a framework for 3D interactive segmentation, supporting intuitive prompts like points, scribbles, bounding boxes, and lasso. Trained on 120+ diverse 3D datasets, it sets a new standard in accuracy, usability, and adaptability for clinical and research applications.
nnUNet
TractSeg
Automatic White Matter Bundle Segmentation
trixi
Manage your machine learning experiments with trixi - modular, reproducible, high fashion. An experiment infrastructure optimized for PyTorch, but flexible enough to work for your framework and your tastes.
MIC-DKFZ's Repositories
MIC-DKFZ/nnUNet
MIC-DKFZ/nnDetection
nnDetection is a self-configuring framework for 3D (volumetric) medical object detection which can be applied to new data sets without manual intervention. It includes guides for 12 data sets that were used to develop and evaluate the performance of the proposed method.
MIC-DKFZ/nnInteractive
nnInteractive is a framework for 3D interactive segmentation, supporting intuitive prompts like points, scribbles, bounding boxes, and lasso. Trained on 120+ diverse 3D datasets, it sets a new standard in accuracy, usability, and adaptability for clinical and research applications.
MIC-DKFZ/dynamic-network-architectures
MIC-DKFZ/Skeleton-Recall
Skeleton Recall Loss for Connectivity Conserving and Resource Efficient Segmentation of Thin Tubular Structures
MIC-DKFZ/napari-nninteractive
MIC-DKFZ/nnssl
MIC-DKFZ/BodyPartRegression
MIC-DKFZ/LesionLocator
LesionLocator is a framework for zero-shot lesion segmentation and longitudinal tumor tracking in 3D full-body imaging.
MIC-DKFZ/MultiTalent
Implemention of the Paper "MultiTalent: A Multi-Dataset Approach to Medical Image Segmentation"
MIC-DKFZ/RTTB
Swiss army knife for radiotherapy analysis
MIC-DKFZ/LongiSeg
MIC-DKFZ/batchgeneratorsv2
MIC-DKFZ/BreastDivider
MIC-DKFZ/radtract
RadTract: enhanced tractometry with radiomics-based imaging biomarkers for improved predictive modelling.
MIC-DKFZ/radioactive
MIC-DKFZ/BraTPRO
MIC-DKFZ/kaggle_BYU_Locating_Bacterial-Flagellar_Motors_2025_solution
MIC-DKFZ/miccai2024_midi-b-submission
MIC-DKFZ/deki-smpc
MIC-DKFZ/napari-data-inspection
MIC-DKFZ/napari_toolkit
MIC-DKFZ/deki-smpc-server
MIC-DKFZ/ScribbleBench
[MICCAI 2025] Revisiting 3D Medical Scribble Supervision: Benchmarking Beyond Cardiac Segmentation
MIC-DKFZ/aorta-aneurysm-assessment
MIC-DKFZ/Temporal-Flow-Matching
MIC-DKFZ/VPE-in-Radiology
MIC-DKFZ/autoPET-interactive
MIC-DKFZ/confly
MIC-DKFZ/nnDetection-finetuning