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Dorsal hand vein segmentation using Vein-Generative Adversarial Network (V-GAN) Model

Difficulty in achieving intravenous access in some patients is a clinical problem due to extreme age, body size, and chronic disease patients. In biometric identification, hand vein patterns are useful when other external identifiers are more prone to be damaged or forged. To overcome these problems...

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Main Authors:	Marlina, Yakno, Junita, Mohamad-Saleh, Mohd Zamri, Ibrahim
Format:	Conference or Workshop Item
Language:	English English
Published:	Springer Science and Business Media Deutschland GmbH 2022
Subjects:	T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/39631/1/Dorsal%20Hand%20Vein%20Segmentation%20Using%20Vein-Generative%20Adversarial.pdf http://umpir.ump.edu.my/id/eprint/39631/2/Dorsal%20hand%20vein%20segmentation%20using%20Vein-Generative%20Adversarial%20Network%20%28V-GAN%29%20Model_ABS.pdf http://umpir.ump.edu.my/id/eprint/39631/ https://doi.org/10.1007/978-981-16-8129-5_89
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id	my.ump.umpir.39631
record_format	eprints
spelling	my.ump.umpir.396312023-12-13T03:34:03Z http://umpir.ump.edu.my/id/eprint/39631/ Dorsal hand vein segmentation using Vein-Generative Adversarial Network (V-GAN) Model Marlina, Yakno Junita, Mohamad-Saleh Mohd Zamri, Ibrahim T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Difficulty in achieving intravenous access in some patients is a clinical problem due to extreme age, body size, and chronic disease patients. In biometric identification, hand vein patterns are useful when other external identifiers are more prone to be damaged or forged. To overcome these problems, near-infrared dorsal hand vein images are captured and segmented for vein extraction. However, the segmentation process becomes more challenging when the infrared im- ages suffer from extremely low contrast and distortion, indirectly affecting the segmentation process. Therefore, this work presents a method for generating an accurate map of dorsal hand vein patterns using deep learning Vein-Generative Adversarial Networks (V-GAN). The performance of V-GAN is measured in terms of accuracy, Area under Curve (AUC), F1-score, sensitivity, specificity, and dice-coefficient. Springer Science and Business Media Deutschland GmbH 2022 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/39631/1/Dorsal%20Hand%20Vein%20Segmentation%20Using%20Vein-Generative%20Adversarial.pdf pdf en http://umpir.ump.edu.my/id/eprint/39631/2/Dorsal%20hand%20vein%20segmentation%20using%20Vein-Generative%20Adversarial%20Network%20%28V-GAN%29%20Model_ABS.pdf Marlina, Yakno and Junita, Mohamad-Saleh and Mohd Zamri, Ibrahim (2022) Dorsal hand vein segmentation using Vein-Generative Adversarial Network (V-GAN) Model. In: Lecture Notes in Electrical Engineering; 11th International Conference on Robotics, Vision, Signal Processing and Power Applications, RoViSP 2021 , 5-6 April 2021 , Virtual, Online. pp. 585-591., 829 LNEE (272139). ISSN 1876-1100 ISBN 978-981168128-8 https://doi.org/10.1007/978-981-16-8129-5_89
institution	Universiti Malaysia Pahang Al-Sultan Abdullah
building	UMPSA Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Pahang Al-Sultan Abdullah
content_source	UMPSA Institutional Repository
url_provider	http://umpir.ump.edu.my/
language	English English
topic	T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Marlina, Yakno Junita, Mohamad-Saleh Mohd Zamri, Ibrahim Dorsal hand vein segmentation using Vein-Generative Adversarial Network (V-GAN) Model
description	Difficulty in achieving intravenous access in some patients is a clinical problem due to extreme age, body size, and chronic disease patients. In biometric identification, hand vein patterns are useful when other external identifiers are more prone to be damaged or forged. To overcome these problems, near-infrared dorsal hand vein images are captured and segmented for vein extraction. However, the segmentation process becomes more challenging when the infrared im- ages suffer from extremely low contrast and distortion, indirectly affecting the segmentation process. Therefore, this work presents a method for generating an accurate map of dorsal hand vein patterns using deep learning Vein-Generative Adversarial Networks (V-GAN). The performance of V-GAN is measured in terms of accuracy, Area under Curve (AUC), F1-score, sensitivity, specificity, and dice-coefficient.
format	Conference or Workshop Item
author	Marlina, Yakno Junita, Mohamad-Saleh Mohd Zamri, Ibrahim
author_facet	Marlina, Yakno Junita, Mohamad-Saleh Mohd Zamri, Ibrahim
author_sort	Marlina, Yakno
title	Dorsal hand vein segmentation using Vein-Generative Adversarial Network (V-GAN) Model
title_short	Dorsal hand vein segmentation using Vein-Generative Adversarial Network (V-GAN) Model
title_full	Dorsal hand vein segmentation using Vein-Generative Adversarial Network (V-GAN) Model
title_fullStr	Dorsal hand vein segmentation using Vein-Generative Adversarial Network (V-GAN) Model
title_full_unstemmed	Dorsal hand vein segmentation using Vein-Generative Adversarial Network (V-GAN) Model
title_sort	dorsal hand vein segmentation using vein-generative adversarial network (v-gan) model
publisher	Springer Science and Business Media Deutschland GmbH
publishDate	2022
url	http://umpir.ump.edu.my/id/eprint/39631/1/Dorsal%20Hand%20Vein%20Segmentation%20Using%20Vein-Generative%20Adversarial.pdf http://umpir.ump.edu.my/id/eprint/39631/2/Dorsal%20hand%20vein%20segmentation%20using%20Vein-Generative%20Adversarial%20Network%20%28V-GAN%29%20Model_ABS.pdf http://umpir.ump.edu.my/id/eprint/39631/ https://doi.org/10.1007/978-981-16-8129-5_89
_version_	1822923983204384768
score	13.232414

Dorsal hand vein segmentation using Vein-Generative Adversarial Network (V-GAN) Model

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