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New dataset ImageCAS-X advances coronary artery segmentation in CCTA

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced ImageCAS-X, a new dataset and benchmark designed to improve the accuracy of coronary artery segmentation in coronary CT angiography (CCTA). This dataset, derived from the publicly available ImageCAS dataset, includes detailed voxel-wise annotations of the vessel lumen, coronary segments, and centerlines for 800 scans. The benchmark evaluates existing lumen segmentation methods against inter-observer variability, providing performance stratification based on various clinical and anatomical factors. ImageCAS-X aims to support the development and validation of advanced methods for lumen segmentation, plaque quantification, and hemodynamic modeling in cardiovascular research. AI

IMPACT Enhances AI capabilities in medical imaging for cardiovascular disease analysis.

RANK_REASON The item describes a new dataset and benchmark for a specific medical imaging task, which falls under research. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New dataset ImageCAS-X advances coronary artery segmentation in CCTA

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The item describes a new dataset and benchmark for a specific medical imaging task, which falls under research. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Kit M. Bransby, Esther {\O}ksnebjerg, Kristoffer Kj{\ae}r, Jacob Kirkeby, Yasmin El Youssef, A\"ida Jim\'enez, Philip R. Pedersson, Martina C. de Knegt, Klaus F. Kofoed, Rasmus R. Paulsen ·

    ImageCAS-X: a dataset and benchmark for coronary artery segmentation and centerline extraction in coronary CT angiography

    arXiv:2608.30404v1 Announce Type: cross Abstract: Accurate segmentation of the coronary vessel lumen is a prerequisite for quantitative assessment of atherosclerotic plaque and perivascular adipose tissue in coronary computed tomography angiography (CCTA). Cardiologists rely on s…

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