Hand blood vessels pattern recognition

This study aimed to address the problem of difficult venous access by proposing a vein feature extraction algorithm for the forearm using transfer learning on a U-net model with EfficientNetB3 as the backbone. The limited availability of forearm Near Infrared (NIR) image datasets and the lack of vei...

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Main Author: Tan, Xuan Qing
Format: Final Year Project / Dissertation / Thesis
Published: 2023
Subjects:
Online Access:http://eprints.utar.edu.my/5817/
http://eprints.utar.edu.my/5817/1/MH_1903950_Final_TAN_XUAN_QING.pdf
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author Tan, Xuan Qing
author_facet Tan, Xuan Qing
author_sort Tan, Xuan Qing
building UTAR Institutional Repository
collection Online Access
description This study aimed to address the problem of difficult venous access by proposing a vein feature extraction algorithm for the forearm using transfer learning on a U-net model with EfficientNetB3 as the backbone. The limited availability of forearm Near Infrared (NIR) image datasets and the lack of vein feature extraction algorithms focused on the forearm part were the main research problems. To evaluate the proposed model, the NTUIFDB v1 dataset containing 250 NIR forearm images was used and the performance was measured using Dice Coefficient and Jaccard Index. The results showed that the proposed model achieved an 83.56% Dice Coefficient and 71.76% Jaccard Index, outperforming four handcrafted techniques tested and other pre-trained models. This research contributes to the field by being the first to implement transfer learning on the NTUIFDB v1 dataset and provides a baseline for future studies to improve the proposed model. The proposed algorithm could aid in improving the success rate of venipuncture in patients with difficult venous access, such as pediatrics, geriatrics, obesity, and dark skin tone patients.
first_indexed 2025-11-15T19:39:41Z
format Final Year Project / Dissertation / Thesis
id utar-5817
institution Universiti Tunku Abdul Rahman
institution_category Local University
last_indexed 2025-11-15T19:39:41Z
publishDate 2023
recordtype eprints
repository_type Digital Repository
spelling utar-58172023-08-08T14:35:23Z Hand blood vessels pattern recognition Tan, Xuan Qing TJ Mechanical engineering and machinery This study aimed to address the problem of difficult venous access by proposing a vein feature extraction algorithm for the forearm using transfer learning on a U-net model with EfficientNetB3 as the backbone. The limited availability of forearm Near Infrared (NIR) image datasets and the lack of vein feature extraction algorithms focused on the forearm part were the main research problems. To evaluate the proposed model, the NTUIFDB v1 dataset containing 250 NIR forearm images was used and the performance was measured using Dice Coefficient and Jaccard Index. The results showed that the proposed model achieved an 83.56% Dice Coefficient and 71.76% Jaccard Index, outperforming four handcrafted techniques tested and other pre-trained models. This research contributes to the field by being the first to implement transfer learning on the NTUIFDB v1 dataset and provides a baseline for future studies to improve the proposed model. The proposed algorithm could aid in improving the success rate of venipuncture in patients with difficult venous access, such as pediatrics, geriatrics, obesity, and dark skin tone patients. 2023 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/5817/1/MH_1903950_Final_TAN_XUAN_QING.pdf Tan, Xuan Qing (2023) Hand blood vessels pattern recognition. Final Year Project, UTAR. http://eprints.utar.edu.my/5817/
spellingShingle TJ Mechanical engineering and machinery
Tan, Xuan Qing
Hand blood vessels pattern recognition
title Hand blood vessels pattern recognition
title_full Hand blood vessels pattern recognition
title_fullStr Hand blood vessels pattern recognition
title_full_unstemmed Hand blood vessels pattern recognition
title_short Hand blood vessels pattern recognition
title_sort hand blood vessels pattern recognition
topic TJ Mechanical engineering and machinery
url http://eprints.utar.edu.my/5817/
http://eprints.utar.edu.my/5817/1/MH_1903950_Final_TAN_XUAN_QING.pdf