Vein recognition using CNN / Wan Nur Nadia Shafiqah Wan Mohd Rohaizan @ Wan Mohd Fakruddin

This project presents a novel approach for vein recognition using Convolutional Neural Networks (CNN). The motivation behind this research is to address the challenges associated with vein detection in healthcare settings, such as the manual and error-prone process of locating veins for procedures l...

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Main Author:	Wan Mohd Rohaizan @ Wan Mohd Fakruddin, Wan Nur Nadia Shafiqah
Format:	Thesis
Language:	English
Published:	2024
Subjects:	Algorithms
Online Access:	https://ir.uitm.edu.my/id/eprint/96289/1/96289.pdf
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id	my-uitm-ir.96289
record_format	uketd_dc
spelling	my-uitm-ir.962892024-06-04T07:20:22Z Vein recognition using CNN / Wan Nur Nadia Shafiqah Wan Mohd Rohaizan @ Wan Mohd Fakruddin 2024 Wan Mohd Rohaizan @ Wan Mohd Fakruddin, Wan Nur Nadia Shafiqah Algorithms This project presents a novel approach for vein recognition using Convolutional Neural Networks (CNN). The motivation behind this research is to address the challenges associated with vein detection in healthcare settings, such as the manual and error-prone process of locating veins for procedures like blood draws and IV insertions. The methodology employed in this project involved collecting a dataset of forearm near-infrared (NIR) images, preprocessing the data, and training a CNN model to accurately identify and classify veins. The findings of this study demonstrate the effectiveness and novelty of using CNNs for vein recognition, achieving high accuracy rates in identifying veins in various settings. The actual work performed included data collection from the GitHub repository, implementation of the CNN algorithm, training the model, and evaluating its performance. The results obtained showcase the potential of CNN-based vein recognition systems in improving the success rate of vein punctures, enhancing patient safety, and optimizing healthcare practices. This project contributes to the field by providing innovative insights and solutions to vein recognition, opening avenues for further advancements in medical imaging and healthcare technologies. 2024 Thesis https://ir.uitm.edu.my/id/eprint/96289/ https://ir.uitm.edu.my/id/eprint/96289/1/96289.pdf text en public degree Universiti Teknologi MARA, Terengganu College of Computing, Informatics and Mathematics Fadzal, Ahmad Nazmi
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Fadzal, Ahmad Nazmi
topic	Algorithms
spellingShingle	Algorithms Wan Mohd Rohaizan @ Wan Mohd Fakruddin, Wan Nur Nadia Shafiqah Vein recognition using CNN / Wan Nur Nadia Shafiqah Wan Mohd Rohaizan @ Wan Mohd Fakruddin
description	This project presents a novel approach for vein recognition using Convolutional Neural Networks (CNN). The motivation behind this research is to address the challenges associated with vein detection in healthcare settings, such as the manual and error-prone process of locating veins for procedures like blood draws and IV insertions. The methodology employed in this project involved collecting a dataset of forearm near-infrared (NIR) images, preprocessing the data, and training a CNN model to accurately identify and classify veins. The findings of this study demonstrate the effectiveness and novelty of using CNNs for vein recognition, achieving high accuracy rates in identifying veins in various settings. The actual work performed included data collection from the GitHub repository, implementation of the CNN algorithm, training the model, and evaluating its performance. The results obtained showcase the potential of CNN-based vein recognition systems in improving the success rate of vein punctures, enhancing patient safety, and optimizing healthcare practices. This project contributes to the field by providing innovative insights and solutions to vein recognition, opening avenues for further advancements in medical imaging and healthcare technologies.
format	Thesis
qualification_level	Bachelor degree
author	Wan Mohd Rohaizan @ Wan Mohd Fakruddin, Wan Nur Nadia Shafiqah
author_facet	Wan Mohd Rohaizan @ Wan Mohd Fakruddin, Wan Nur Nadia Shafiqah
author_sort	Wan Mohd Rohaizan @ Wan Mohd Fakruddin, Wan Nur Nadia Shafiqah
title	Vein recognition using CNN / Wan Nur Nadia Shafiqah Wan Mohd Rohaizan @ Wan Mohd Fakruddin
title_short	Vein recognition using CNN / Wan Nur Nadia Shafiqah Wan Mohd Rohaizan @ Wan Mohd Fakruddin
title_full	Vein recognition using CNN / Wan Nur Nadia Shafiqah Wan Mohd Rohaizan @ Wan Mohd Fakruddin
title_fullStr	Vein recognition using CNN / Wan Nur Nadia Shafiqah Wan Mohd Rohaizan @ Wan Mohd Fakruddin
title_full_unstemmed	Vein recognition using CNN / Wan Nur Nadia Shafiqah Wan Mohd Rohaizan @ Wan Mohd Fakruddin
title_sort	vein recognition using cnn / wan nur nadia shafiqah wan mohd rohaizan @ wan mohd fakruddin
granting_institution	Universiti Teknologi MARA, Terengganu
granting_department	College of Computing, Informatics and Mathematics
publishDate	2024
url	https://ir.uitm.edu.my/id/eprint/96289/1/96289.pdf
_version_	1804889983014666240

Vein recognition using CNN / Wan Nur Nadia Shafiqah Wan Mohd Rohaizan @ Wan Mohd Fakruddin

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