Cardiac-CT

Dataset accompanying the paper:

A Unified Framework for Comprehensive Cardiac CT Segmentation and Phenotyping: Human-in-the-Loop Data Annotation, Vision Foundation Model Development, Multicenter Evaluation and Clinical Validation

Pooya Mohammadi Kazaj, Leo Fridolin Weber, Wen Xie, Seyed Amir Ahmad Safavi-Naini, Anselm Stark, Giovanni Baj, Ali Mokhtari, Toshiya Yoshida, Christoph Ryffel, Taishi Okuno, Yoshihiro Akashi, Ronny R. Buechel, Thomas Pilgrim, Waldo Valenzuela, George C. M. Siontis, Xiaowei Xu, Moritz Hundertmark, Stephan Windecker, Christoph Grani, Isaac Shiri

Paper: https://arxiv.org/abs/2607.11287

About

This repository will host the expert-annotated cardiac CT dataset described in the paper above, along with associated resources (segmentation labels, model weights, and a CT augmentation library).

Dataset overview

• 1,598 expert-annotated cardiac CT cases across 14 distinct cardiac structures
  • 1,000 cases for training
  • 598 cases held out as external test data
• 5 external multicenter test datasets used for evaluation
• 60,000 unlabeled cardiac CT scans used to pretrain a self-supervised vision foundation model
• Human-in-the-loop annotation pipeline for label quality control

Released in this repository: the 1,000 training cases — originally sourced from the ImageCAS coronary CT angiography dataset and extended with expert annotations for the remaining 13 cardiac structures — together with the full MM-WHS test dataset (20 cases).

Dataset structure

(Placeholder — update paths/filenames to match what you actually upload.)

Path	Description
Train(ImageCAS)/images	Training CT volumes (.nii.gz), sourced from ImageCAS
Train(ImageCAS)/segmentations/	Training segmentation masks for the 14 cardiac structures (.nii.gz)
ExtTest-5(MM-WHS)/segmentations/	MM-WHS external test segmentation masks (ours)

Note: We do not redistribute the MM-WHS CT images themselves. To get the corresponding images for ExtTest-5(MM-WHS), request them directly from the official MM-WHS challenge website: https://zmiclab.github.io/zxh/0/mmwhs/

Preview

Overview of the annotation and modeling pipeline.

Coronary artery centerline extraction.

Three-dimensional STL meshes of the segmented cardiac structures.

Qualitative comparison of segmentation outputs across models and external test sets.

Status

The dataset is currently closed source and will be released here once the paper is published. Until then, it is available upon request.

Citation

If you use this dataset, please cite:

@article{mohammadikazaj2026unified,
  author  = {Mohammadi Kazaj, Pooya and Weber, Leo Fridolin and Xie, Wen and Safavi-Naini, Seyed Amir Ahmad and Stark, Anselm and Baj, Giovanni and Mokhtari, Ali and Yoshida, Toshiya and Ryffel, Christoph and Okuno, Taishi and Akashi, Yoshihiro and Buechel, Ronny R. and Pilgrim, Thomas and Valenzuela, Waldo and Siontis, George C. M. and Xu, Xiaowei and Hundertmark, Moritz and Windecker, Stephan and Grani, Christoph and Shiri, Isaac},
  title   = {A Unified Framework for Comprehensive Cardiac CT Segmentation and Phenotyping: Human-in-the-Loop Data Annotation, Vision Foundation Model Development, Multicenter Evaluation and Clinical Validation},
  journal = {arXiv preprint arXiv:2607.11287},
  year    = {2026}
}

References

This dataset builds on prior public datasets, in addition to the main paper above:

1. Zeng A, Wu C, Lin G, Xie W, Hong J, Huang M, Zhuang J, Bi S, Pan D, Ullah N, Khan KN, Wang T, Shi Y, Li X, Xu X. "ImageCAS: A large-scale dataset and benchmark for coronary artery segmentation based on computed tomography angiography images." Computerized Medical Imaging and Graphics, 2023;109:102287. DOI
2. Zhuang X, Li L, Payer C, Štern D, Urschler M, Heinrich MP, Oster J, Wang C, Smedby Ö, Bian C, Yang X, Heng PA, Mortazi A, Bagci U, Yang G, Sun C, Galisot G, Ramel JY, Brouard T, Tong Q, Si W, Liao X, Zeng G, Shi Z, Zheng G, Wang C, MacGillivray T, Newby D, Rhode K, Ourselin S, Mohiaddin R, Keegan J, Firmin D, Yang G. "Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge." Medical Image Analysis, 2019;58:101537. DOI
3. Zhuang X, Shen J. "Multi-scale patch and multi-modality atlases for whole heart segmentation of MRI." Medical Image Analysis, 2016;31:77–87. DOI