Optical coherence tomography angiography for vessel segmentation

Optical Coherence Tomography Angiography (OCTA) is a non-invasive imaging technique that has gained prominence in the diagnosis and management of various ocular diseases. Accurate vessel segmentation in OCTA images is crucial for the quantitative analysis of vascular structures. This study propos...

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Bibliographic Details
Main Author: Zhang, Mengyuan
Other Authors: Liu Linbo
Format: Final Year Project (FYP)
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/167445
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author Zhang, Mengyuan
author2 Liu Linbo
author_facet Liu Linbo
Zhang, Mengyuan
author_sort Zhang, Mengyuan
collection NTU
description Optical Coherence Tomography Angiography (OCTA) is a non-invasive imaging technique that has gained prominence in the diagnosis and management of various ocular diseases. Accurate vessel segmentation in OCTA images is crucial for the quantitative analysis of vascular structures. This study proposes a novel approach for OCTA vessel segmentation using Hessian-based filtering and local mean enhancement. The method involves pre-processing the images, extracting the Foveal Avascular Zone (FAZ) region, and applying a Hessian filter to enhance blood vessels. Local mean computation and thresholding techniques are employed for binary vessel segmentation and further enhancement. The proposed method was evaluated on a dataset of ten OCTA images, demonstrating promising results in vessel segmentation with improved accuracy and efficiency compared to existing techniques. This approach has potential applications in clinical practice and research, contributing to the better understanding and management of ocular diseases.
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spelling ntu-10356/1674452023-07-07T17:17:25Z Optical coherence tomography angiography for vessel segmentation Zhang, Mengyuan Liu Linbo School of Electrical and Electronic Engineering LIULINBO@ntu.edu.sg Engineering::Electrical and electronic engineering Optical Coherence Tomography Angiography (OCTA) is a non-invasive imaging technique that has gained prominence in the diagnosis and management of various ocular diseases. Accurate vessel segmentation in OCTA images is crucial for the quantitative analysis of vascular structures. This study proposes a novel approach for OCTA vessel segmentation using Hessian-based filtering and local mean enhancement. The method involves pre-processing the images, extracting the Foveal Avascular Zone (FAZ) region, and applying a Hessian filter to enhance blood vessels. Local mean computation and thresholding techniques are employed for binary vessel segmentation and further enhancement. The proposed method was evaluated on a dataset of ten OCTA images, demonstrating promising results in vessel segmentation with improved accuracy and efficiency compared to existing techniques. This approach has potential applications in clinical practice and research, contributing to the better understanding and management of ocular diseases. Bachelor of Engineering (Electrical and Electronic Engineering) 2023-05-26T07:09:27Z 2023-05-26T07:09:27Z 2023 Final Year Project (FYP) Zhang, M. (2023). Optical coherence tomography angiography for vessel segmentation. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/167445 https://hdl.handle.net/10356/167445 en A1087-221 application/pdf Nanyang Technological University
spellingShingle Engineering::Electrical and electronic engineering
Zhang, Mengyuan
Optical coherence tomography angiography for vessel segmentation
title Optical coherence tomography angiography for vessel segmentation
title_full Optical coherence tomography angiography for vessel segmentation
title_fullStr Optical coherence tomography angiography for vessel segmentation
title_full_unstemmed Optical coherence tomography angiography for vessel segmentation
title_short Optical coherence tomography angiography for vessel segmentation
title_sort optical coherence tomography angiography for vessel segmentation
topic Engineering::Electrical and electronic engineering
url https://hdl.handle.net/10356/167445
work_keys_str_mv AT zhangmengyuan opticalcoherencetomographyangiographyforvesselsegmentation