{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T08:51:31Z","timestamp":1767689491064,"version":"3.48.0"},"reference-count":46,"publisher":"PeerJ","license":[{"start":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T00:00:00Z","timestamp":1767657600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Tabung Amanah Zakat Multimedia University"},{"name":"Fisabilillah Research & Development Grant Scheme","award":["MMUE\/240156"],"award-info":[{"award-number":["MMUE\/240156"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>\n                    Retinal vascular tortuosity is a clinically relevant biomarker linked to systemic and ocular diseases; however, its quantitative assessment particularly the distinction between arteries and veins remains underexplored in both healthy and pathological conditions. This study investigates tortuosity behavior using three publicly available retinal fundus image datasets: Digital Retinal Images for Vessel Extraction (DRIVE), High-Resolution Fundus (HRF), and Labelled Eye fundus Segmentation-Artery Vein (LES-AV). A standardized analytical pipeline combining curvature-based metrics, breadth-first search (BFS) and Euclidean distance was applied following vessel segmentation, artery-vein separation, skeletonization, and optic disc-based tracing. BFS algorithm was utilized for vessel path tracing, chosen for its robustness and suitability in navigating complex vascular structures with high reproducibility. Five comparative analyses were performed: artery\n                    <jats:italic>vs<\/jats:italic>\n                    . vein tortuosity; healthy\n                    <jats:italic>vs<\/jats:italic>\n                    . diseased eyes (glaucoma and diabetic retinopathy); and cross-dataset comparisons under both healthy and pathological conditions. Across all datasets, veins consistently exhibited higher tortuosity than arteries in healthy eyes, confirmed by large effect sizes (Cohen\u2019s d), despite weak correlation between the two vessel types. Diabetic retinopathy cases showed an amplified artery-vein separation, suggesting disease-induced vascular changes. Glaucomatous eyes exhibited mixed patterns, with HRF artery-vein differences maintained and LES-AV showing diminished separation, partly due to non-normal data distribution. A key finding highlights the significant influence of imaging characteristics especially field of view (FOV) on tortuosity measurement. Datasets with a wider field of view, such as DRIVE and HRF (45\u00b0 FOV, optical disc (OD) positioned nasally), captured more peripheral, tortuous vessels and reported higher tortuosity values. In contrast, the LES-AV dataset with a narrower 30\u00b0 FOV and centered optic disc, resulted in lower tortuosity measurements and weaker artery-vein differentiation. These anatomical and technical differences emphasize the need to handle FOV and orientation settings when designing or comparing tortuosity-based diagnostic studies. In conclusion, retinal vascular tortuosity appears to be a vessel-specific feature which is robust and capable of capturing both pathological and variations in dataset. The findings support its integration into automated diagnostic frameworks and highlight the importance of standardizing imaging parameters particularly FOV and anatomical orientation in future retinal biomarker research.\n                  <\/jats:p>","DOI":"10.7717\/peerj.20561","type":"journal-article","created":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T08:46:23Z","timestamp":1767689183000},"page":"e20561","source":"Crossref","is-referenced-by-count":0,"title":["An improved tortuosity measurement method combining curvature-based, breadth-first search and Euclidean distance for retinal image analysis"],"prefix":"10.7717","volume":"14","author":[{"given":"Nur Asyiqin","family":"Amir Hamzah","sequence":"first","affiliation":[{"name":"Centre of Advanced Analytics, Faculty of Engineering and Technology, Multimedia University, Jalan Ayer Keroh Lama, Melaka, Malaysia"},{"name":"Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5808-4348","authenticated-orcid":true,"given":"Wan Mimi Diyana","family":"Wan Zaki","sequence":"additional","affiliation":[{"name":"Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aziah","family":"Ali","sequence":"additional","affiliation":[{"name":"Center for Image and Vision Computing, Faculty of Computing and Informatics, Multimedia University, Cyberjaya, Selangor, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"4443","published-online":{"date-parts":[[2026,1,6]]},"reference":[{"issue":"3","key":"10.7717\/peerj.20561\/ref-1","doi-asserted-by":"publisher","first-page":"1102","DOI":"10.21037\/QIMS-20-557","article-title":"Differential artery-vein analysis in quantitative retinal imaging: a review","volume":"11","author":"Alam","year":"2021","journal-title":"Quantitative Imaging in Medicine and Surgery"},{"key":"10.7717\/peerj.20561\/ref-2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/ISIEA51897.2021.9510005","article-title":"B-COSFIRE and background normalisation for efficient segmentation of retinal vessels","author":"Ali","year":"2021"},{"issue":"3","key":"10.7717\/peerj.20561\/ref-3","doi-asserted-by":"publisher","first-page":"1199","DOI":"10.11591\/ijeecs.v13.i3.pp1199-1207","article-title":"Retinal blood vessel segmentation from retinal image using B-COSFIRE and adaptive thresholding","volume":"13","author":"Ali","year":"2019","journal-title":"Indonesian Journal of Electrical Engineering and Computer Science"},{"issue":"2","key":"10.7717\/peerj.20561\/ref-4","doi-asserted-by":"publisher","first-page":"155","DOI":"10.3390\/app8020155","article-title":"Retinal vessels segmentation techniques and algorithms: a survey","volume":"8","author":"Almotiri","year":"2018","journal-title":"Applied Sciences"},{"issue":"8","key":"10.7717\/peerj.20561\/ref-5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.7717\/peerj.17786","article-title":"Evaluating the potential of retinal photography in chronic kidney disease detection: a review","volume":"12","author":"Amir Hamzah","year":"2024","journal-title":"PeerJ"},{"issue":"18","key":"10.7717\/peerj.20561\/ref-6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/math11183811","article-title":"A comparison of the tortuosity phenomenon in retinal arteries and veins using digital image processing and statistical methods","volume":"11","author":"Badawi","year":"2023","journal-title":"Mathematics"},{"key":"10.7717\/peerj.20561\/ref-7","article-title":"ISODATA: a novel method of data analysis and pattern classification. 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