Real-Time Superficial Vein Imaging System for Observing Abnormalities on Vascular Structures
| dc.contributor.author | Altay, A. | |
| dc.contributor.author | Gumus, A. | |
| dc.date.accessioned | 2024-03-03T16:41:35Z | |
| dc.date.available | 2024-03-03T16:41:35Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | Circulatory system abnormalities might be an indicator of diseases or tissue damage. Early detection of vascular abnormalities might have an important role during treatment and also raise the patient’s awareness. Current detection methods for vascular imaging are high-cost, invasive, and mostly radiation-based. In this study, a low-cost and portable microcomputer-based tool has been developed as a Near-Infrared (NIR) superficial vascular imaging device. The device uses NIR Light-Emitting Diode (LED) light at 850 nm along with other electronic and optical components. It operates as a non-contact and safe infrared (IR) imaging method in real-time. Image and video analysis are carried out using OpenCV (Open-Source Computer Vision), a library of programming functions mainly used in computer vision. Various tests were carried out to optimize the imaging system and set up a suitable external environment. To test the performance of the device, the images taken from three diabetic volunteers, who are expected to have abnormalities in the vascular structure due to the possibility of deformation caused by high glucose levels in the blood, were compared with the images taken from two non-diabetic volunteers. As a result, tortuosity was observed successfully in the superficial vascular structures, where the results need to be interpreted by the medical experts in the field to understand the underlying reasons. Although this study is an engineering study and does not have an intention to diagnose any diseases, the developed system here might assist healthcare personnel in early diagnosis and treatment follow-up for vascular structures and may enable further opportunities. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. | en_US |
| dc.identifier.doi | 10.1007/s11042-023-16251-7 | |
| dc.identifier.issn | 1380-7501 | |
| dc.identifier.scopus | 2-s2.0-85165877737 | |
| dc.identifier.uri | https://doi.org/10.1007/s11042-023-16251-7 | |
| dc.language.iso | en | en_US |
| dc.publisher | Springer | en_US |
| dc.relation.ispartof | Multimedia Tools and Applications | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Computer Vision | en_US |
| dc.subject | Medical Imaging System | en_US |
| dc.subject | Microcomputer | en_US |
| dc.subject | Real-Time Video Processing | en_US |
| dc.subject | Superficial Vein Imaging | en_US |
| dc.title | Real-Time Superficial Vein Imaging System for Observing Abnormalities on Vascular Structures | en_US |
| dc.type | Article | en_US |
| dspace.entity.type | Publication | |
| gdc.author.institutional | … | |
| gdc.author.institutional | Gümüş, Abdurrahman | |
| gdc.author.scopusid | 57430759300 | |
| gdc.author.scopusid | 35315599800 | |
| gdc.bip.impulseclass | C5 | |
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| gdc.coar.access | metadata only access | |
| gdc.coar.type | text::journal::journal article | |
| gdc.collaboration.industrial | false | |
| gdc.description.department | İzmir Institute of Technology | en_US |
| gdc.description.departmenttemp | [Altay] Ayse, Department of Electrical and Electronic Engineering, Izmir Yüksek Teknoloji Enstitüsü, Izmir, Turkey; [Gumus] Abdurrahman, Department of Electrical and Electronic Engineering, Izmir Yüksek Teknoloji Enstitüsü, Izmir, Turkey | en_US |
| gdc.description.endpage | 21064 | en_US |
| gdc.description.issue | 7 | en_US |
| gdc.description.publicationcategory | Diğer | en_US |
| gdc.description.scopusquality | N/A | |
| gdc.description.startpage | 21045 | en_US |
| gdc.description.volume | 83 | en_US |
| gdc.description.woscitationindex | Science Citation Index Expanded | |
| gdc.description.wosquality | N/A | |
| gdc.identifier.openalex | W4385272326 | |
| gdc.identifier.wos | WOS:001043237000002 | |
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| gdc.oaire.keywords | FOS: Computer and information sciences | |
| gdc.oaire.keywords | Computer Vision and Pattern Recognition (cs.CV) | |
| gdc.oaire.keywords | Computer Science - Computer Vision and Pattern Recognition | |
| gdc.oaire.popularity | 2.588463E-9 | |
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| gdc.oaire.sciencefields | 03 medical and health sciences | |
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