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Computer-assisted pterygium screening system: a review

Pterygium is an eye condition that causes the fibrovascular tissues to grow towards the corneal region. At the early stage, it is not a harmful condition, except for slight discomfort for the patients. However, it will start to affect the eyesight of the patient once the tissues encroach towards the...

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Main Authors: Abdani, Siti Raihanah, Zulkifley, Mohd Asyraf, Shahrimin, Mohamad Ibrani, Zulkifley, Nuraisyah Hani
Format: Article
Published: MDPI 2022
Online Access:http://psasir.upm.edu.my/id/eprint/100774/
https://www.mdpi.com/2075-4418/12/3/639
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spelling my.upm.eprints.1007742023-09-11T01:53:01Z http://psasir.upm.edu.my/id/eprint/100774/ Computer-assisted pterygium screening system: a review Abdani, Siti Raihanah Zulkifley, Mohd Asyraf Shahrimin, Mohamad Ibrani Zulkifley, Nuraisyah Hani Pterygium is an eye condition that causes the fibrovascular tissues to grow towards the corneal region. At the early stage, it is not a harmful condition, except for slight discomfort for the patients. However, it will start to affect the eyesight of the patient once the tissues encroach towards the corneal region, with a more serious impact if it has grown into the pupil region. Therefore, this condition needs to be identified as early as possible to halt its growth, with the use of simple eye drops and sunglasses. One of the associated risk factors for this condition is a low educational level, which explains the reason that the majority of the patients are not aware of this condition. Hence, it is important to develop an automated pterygium screening system based on simple imaging modalities such as a mobile phone camera so that it can be assessed by many people. During the early stage of automated pterygium screening system development, conventional machine learning techniques such as support vector machines and artificial neural networks are the de facto algorithms to detect the presence of pterygium tissues. However, with the arrival of the deep learning era, coupled with the availability of large training data, deep learning networks have replaced the conventional networks in screening for the pterygium condition. The deep learning networks have been successfully implemented for three major purposes, which are to classify an image regarding whether there is the presence of pterygium tissues or not, to localize the lesion tissues through object detection methodology, and to semantically segment the lesion tissues at the pixel level. This review paper summarizes the type, severity, risk factors, and existing state-of-the-art technology in automated pterygium screening systems. A few available datasets are also discussed in this paper for both classification and segmentation tasks. In conclusion, a computer-assisted pterygium screening system will benefit many people all over the world, especially in alerting them to the possibility of having this condition so that preventive actions can be advised at an early stage. MDPI 2022-03-05 Article PeerReviewed Abdani, Siti Raihanah and Zulkifley, Mohd Asyraf and Shahrimin, Mohamad Ibrani and Zulkifley, Nuraisyah Hani (2022) Computer-assisted pterygium screening system: a review. Diagnostics, 12 (3). art. no. 639. pp. 1-18. ISSN 2075-4418 https://www.mdpi.com/2075-4418/12/3/639 10.3390/diagnostics12030639
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description Pterygium is an eye condition that causes the fibrovascular tissues to grow towards the corneal region. At the early stage, it is not a harmful condition, except for slight discomfort for the patients. However, it will start to affect the eyesight of the patient once the tissues encroach towards the corneal region, with a more serious impact if it has grown into the pupil region. Therefore, this condition needs to be identified as early as possible to halt its growth, with the use of simple eye drops and sunglasses. One of the associated risk factors for this condition is a low educational level, which explains the reason that the majority of the patients are not aware of this condition. Hence, it is important to develop an automated pterygium screening system based on simple imaging modalities such as a mobile phone camera so that it can be assessed by many people. During the early stage of automated pterygium screening system development, conventional machine learning techniques such as support vector machines and artificial neural networks are the de facto algorithms to detect the presence of pterygium tissues. However, with the arrival of the deep learning era, coupled with the availability of large training data, deep learning networks have replaced the conventional networks in screening for the pterygium condition. The deep learning networks have been successfully implemented for three major purposes, which are to classify an image regarding whether there is the presence of pterygium tissues or not, to localize the lesion tissues through object detection methodology, and to semantically segment the lesion tissues at the pixel level. This review paper summarizes the type, severity, risk factors, and existing state-of-the-art technology in automated pterygium screening systems. A few available datasets are also discussed in this paper for both classification and segmentation tasks. In conclusion, a computer-assisted pterygium screening system will benefit many people all over the world, especially in alerting them to the possibility of having this condition so that preventive actions can be advised at an early stage.
format Article
author Abdani, Siti Raihanah
Zulkifley, Mohd Asyraf
Shahrimin, Mohamad Ibrani
Zulkifley, Nuraisyah Hani
spellingShingle Abdani, Siti Raihanah
Zulkifley, Mohd Asyraf
Shahrimin, Mohamad Ibrani
Zulkifley, Nuraisyah Hani
Computer-assisted pterygium screening system: a review
author_facet Abdani, Siti Raihanah
Zulkifley, Mohd Asyraf
Shahrimin, Mohamad Ibrani
Zulkifley, Nuraisyah Hani
author_sort Abdani, Siti Raihanah
title Computer-assisted pterygium screening system: a review
title_short Computer-assisted pterygium screening system: a review
title_full Computer-assisted pterygium screening system: a review
title_fullStr Computer-assisted pterygium screening system: a review
title_full_unstemmed Computer-assisted pterygium screening system: a review
title_sort computer-assisted pterygium screening system: a review
publisher MDPI
publishDate 2022
url http://psasir.upm.edu.my/id/eprint/100774/
https://www.mdpi.com/2075-4418/12/3/639
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score 13.211869

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