ArticleJournal of imaging2026
IPSM-UNet: An Inverted Pyramid-Shaped U-Net++ Architecture with Multi-Resolution Information Interaction for Coronary Artery Segmentation.
Article in Journal of imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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Abstract
Accurate coronary artery segmentation is essential for diagnosis and interventional planning, but conventional U-shaped networks often miss thin, low-contrast vessels and break vessel continuity. We propose Inverted Pyramid-Shaped Multi-resolution U-Net (IPSM-UNet), a dual U-Net++ architecture with multi-resolution feature interaction, feature aggregation, and layer-wise deep supervision. The method is evaluated on DRIVE, CHASE_DB1, DCA1, and an internal coronary angiography dataset. IPSM-UNet achieves competitive or better performance across datasets, including F1 = 0.8310 and Acc = 0.9707 on DRIVE, Se = 0.8792 and Acc = 0.9745 on CHASE_DB1, F1 = 0.8043 and Acc = 0.9793 on DCA1, and Se = 0.8741, F1 = 0.8590, and Acc = 0.9879 on the internal dataset. IPSM-UNet improves vessel continuity and overall segmentation quality, particularly for small-caliber vessels, and supports downstream coronary analysis.
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