Coronary Artery Vessel Tree Segmentation Using Transfer Learning from CT Angiography Images

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dc.contributor.authorKhafagy, Zeiad
dc.contributor.authorOksuz, Ilkay
dc.date.accessioned2026-04-04T18:55:51Z
dc.date.available2026-04-04T18:55:51Z
dc.date.issued2025
dc.departmentİstanbul Bilgi Üniversitesi
dc.description33rd Conference on Signal Processing and Communications Applications-SIU-Annual -- JUN 25-28, 2025 -- Istanbul, TURKIYE
dc.description.abstractAutomatic segmentation of coronary arteries is crucial for precise diagnosis and treatment planning in cardiovascular imaging. In this study, we employ a deep learning framework based on the nn-UNet framework for coronary artery segmentation. Our approach leverages annotated datasets, namely ASOCA and ImageCAS, to enhance segmentation accuracy using transfer learning. Additionally, we apply post-processing techniques to further refine the segmentation results. Evaluation on both datasets demonstrates improvements in segmentation accuracy, highlighting the effectiveness of our method in handling complex anatomical structures such as coronary arteries. Notably, the incorporation of transfer learning led to a significant enhancement in segmentation performance, underscoring its value in coronary arteries segmentation. The proposed approach leveraging from transfer learning and post-processing achieves Dice score of 0.856 and a Hausorf distance of 14.5 on the ASOCA dataset.
dc.description.sponsorshipInstitute of Electrical and Electronics Engineers Inc
dc.identifier.doi10.1109/SIU66497.2025.11112326
dc.identifier.doi10.1109/SIU66497.2025.11112326
dc.identifier.isbn979-8-3315-6656-2
dc.identifier.isbn979-8-3315-6655-5
dc.identifier.issn2165-0608
dc.identifier.scopus2-s2.0-105015419751
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/SIU66497.2025.11112326
dc.identifier.urihttps://hdl.handle.net/11411/10591
dc.identifier.wosWOS:001575462500304
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIeee
dc.relation.ispartof2025 33Rd Signal Processing and Communications Applications Conference, Siu
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20260402
dc.snmzKA_Scopus_20260402
dc.subjectCoronary Arteries
dc.subjectDeep Learning
dc.subjectConvolutional Neural Network
dc.subjectMedical Image Analysis
dc.titleCoronary Artery Vessel Tree Segmentation Using Transfer Learning from CT Angiography Images
dc.typeConference Object

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