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
gdc.bip.influenceclass C5
gdc.bip.popularityclass C5
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
gdc.index.type WoS
gdc.index.type Scopus
gdc.oaire.diamondjournal false
gdc.oaire.impulse 0.0
gdc.oaire.influence 2.635068E-9
gdc.oaire.isgreen true
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
gdc.oaire.publicfunded false
gdc.oaire.sciencefields 03 medical and health sciences
gdc.oaire.sciencefields 0302 clinical medicine
gdc.oaire.sciencefields 0103 physical sciences
gdc.oaire.sciencefields 01 natural sciences
gdc.openalex.collaboration National
gdc.openalex.fwci 0.30905497
gdc.openalex.normalizedpercentile 0.58
gdc.opencitations.count 0
gdc.plumx.mendeley 10
gdc.plumx.scopuscites 1
gdc.scopus.citedcount 1
gdc.wos.citedcount 1
relation.isAuthorOfPublication.latestForDiscovery ce5ce1e2-17ef-4da2-946d-b7a26e44e461
relation.isOrgUnitOfPublication.latestForDiscovery 9af2b05f-28ac-4003-8abe-a4dfe192da5e

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Name:
s11042-023-16251-7.pdf
Size:
8.98 MB
Format:
Adobe Portable Document Format
Description:
Article