A public cardiac CT dataset featuring the left atrial appendage

Bjoern Hansen, Jonas Pedersen, Klaus F. Kofoed, Oscar Camara, Rasmus R. Paulsen +1 more
10/7/2025
cs.CVcs.AI

No official code found. Best implementation: Bjonze/Public-Cardiac-CT-Dataset (24 stars, MIT, last commit 2025-10-16).

Abstract

Despite the success of advanced segmentation frameworks such as TotalSegmentator (TS), accurate segmentations of the left atrial appendage (LAA), coronary arteries (CAs), and pulmonary veins (PVs) remain a significant challenge in medical imaging. In this work, we present the first open-source, anatomically coherent dataset of curated, high-resolution segmentations for these structures, supplemented with whole-heart labels produced by TS on the publicly available ImageCAS dataset consisting of 1000 cardiac computed tomography angiography (CCTA) scans. One purpose of the data set is to foster novel approaches to the analysis of LAA morphology. LAA segmentations on ImageCAS were generated using a state-of-the-art segmentation framework developed specifically for high resolution LAA segmentation. We trained the network on a large private dataset with manual annotations provided by medical readers guided by a trained cardiologist and transferred the model to ImageCAS data. CA labels were improved from the original ImageCAS annotations, while PV segmentations were refined from TS outputs. In addition, we provide a list of scans from ImageCAS that contains common data flaws such as step artefacts, LAAs extending beyond the scanner's field of view, and other types of data defects.

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Code Implementations(1)

MIT

Official GitHub repo for the article "A Public Cardiac CT Dataset Featuring the Left Atrial Appendage" published at the STACOM 2025 MICCAI workshop.

241PythonAug 27, 20251 years agoMIT

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Cite this paper

@article{hansen2025public,
  title  = {A public cardiac CT dataset featuring the left atrial appendage},
  author = {Bjoern Hansen and Jonas Pedersen and Klaus F. Kofoed and Oscar Camara and Rasmus R. Paulsen and Kristine Soerensen},
  year   = {2025},
  eprint = {2510.06090},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2510.06090v1}
}

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