most citedDeep Learning Pipeline for Fully Automated Myocardial Infarct Segmentation from Clinical Cardiac MR Scans

1 citations · 1 across the 1 of their papers we have counts for

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eess.IV2025★ 1 cited

Deep Learning Pipeline for Fully Automated Myocardial Infarct Segmentation from Clinical Cardiac MR Scans

Matthias Schwab, Mathias Pamminger, Christian Kremser +2

Purpose: To develop and evaluate a deep learning-based method that allows to perform myocardial infarct segmentation in a fully-automated way. Materials and Methods: For this retro…

eess.IV2025

Multi-Class Segmentation of Aortic Branches and Zones in Computed Tomography Angiography: The AortaSeg24 Challenge

Muhammad Imran, Jonathan R. Krebs, Vishal Balaji Sivaraman +60

Multi-class segmentation of the aorta in computed tomography angiography (CTA) scans is essential for diagnosing and planning complex endovascular treatments for patients with aort…