VAP2D: A Program for Quantitative Analysis of 2D Vessel Images
| dc.contributor.author | Kaya, Samet | |
| dc.contributor.author | Dık, Sümeyye Zülal | |
| dc.contributor.author | Kiraz, Berna | |
| dc.date.accessioned | 2026-09-11T12:23:27Z | |
| dc.date.issued | 2026 | |
| dc.department | FSM Vakıf Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü | |
| dc.description.abstract | Vessel analysis is crucial in fields such as medical imaging and biomedical engineering. This study introduces VAP2D (two-dimensional vessel analysis program), an opensource, cross-platform, user-friendly software available on GitHub for the quantitative analysis of 2D vessel images. VAP2D enables the detection of branch points and endpoints, the calculation of vessel lengths and densities, and the generation of detailed reports. The software supports both traditional image processing techniques and deep learningbased methods, offering users flexibility based on data type and image quality. In addition, it incorporates essential pre-processing steps, including noise removal, segmentation, and skeletonization, to optimize the analysis of raw images. VAP2D has been rigorously tested to accurately detect branch points, endpoints, vessel densities, and lengths. Its modular structure, graphical user interface (GUI), and ability to export results in CSV or PDF formats make it a practical and adaptable tool for researchers and laboratory technicians. By bridging the gap between scientific research and practical applications, VAP2D provides a reliable platform for vessel analysis in medical imaging, biomedical engineering, and beyond. | |
| dc.identifier.citation | KAYA, Samet, Sümeyye Zülal DIK & Berna KİRAZ. "VAP2D: A Program for Quantitative Analysis of 2D Vessel Images". Journal of Open Research Software, 14.1 (2026): 1-11. | |
| dc.identifier.doi | 10. 5334/jors.655 | |
| dc.identifier.endpage | 11 | |
| dc.identifier.issue | 1 | |
| dc.identifier.orcid | https://orcid.org/0009-0007-0964-686X | |
| dc.identifier.orcid | https://orcid.org/0009-0002-5629-6413 | |
| dc.identifier.orcid | https://orcid.org/0000-0002-8428-3217 | |
| dc.identifier.scopus | 2-s2.0-105047780155 | |
| dc.identifier.scopusquality | Q3 | |
| dc.identifier.startpage | 1 | |
| dc.identifier.uri | https://reference-global.com/article/10.5334/jors.655 | |
| dc.identifier.uri | https://hdl.handle.net/11352/6271 | |
| dc.identifier.volume | 14 | |
| dc.indekslendigikaynak | Scopus | |
| dc.language.iso | en | |
| dc.publisher | Ubiquity Press | |
| dc.relation.ispartof | Journal of Open Research Software | |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.subject | Medical Imaging | |
| dc.subject | Vessel Analysis Program | |
| dc.subject | Computer Vision | |
| dc.subject | Deep-Learning Object Detection | |
| dc.subject | Vascular Imaging | |
| dc.subject | Digital Pathology | |
| dc.title | VAP2D: A Program for Quantitative Analysis of 2D Vessel Images | |
| dc.type | Article |










