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An Algorithm for Shrinking Blood Receptacles using Retinal Internal Pictures for Clinical Characteristics Measurement

Blood vessels; Diagnosis; Information filtering; Ophthalmology; Photography; Characteristic measurements; Clinical characteristic measurement; Clinical characteristics; Filtering algorithm; Fundus photographs; Internal picture for retinal; Manual techniques; Morphological filtering; Morphological fi...

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Main Authors: Abdulsahib A.A., Mahmoud M.A., Al-Hasnawi S.A.
Other Authors: 57222592694
Format: Article
Published: Science and Information Organization 2023
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spelling my.uniten.dspace-270732023-05-29T17:39:18Z An Algorithm for Shrinking Blood Receptacles using Retinal Internal Pictures for Clinical Characteristics Measurement Abdulsahib A.A. Mahmoud M.A. Al-Hasnawi S.A. 57222592694 55247787300 57962503400 Blood vessels; Diagnosis; Information filtering; Ophthalmology; Photography; Characteristic measurements; Clinical characteristic measurement; Clinical characteristics; Filtering algorithm; Fundus photographs; Internal picture for retinal; Manual techniques; Morphological filtering; Morphological filtering algorithm; Segmentation vessel / shrinking blood receptacle; Blood The manual technique that might use for shrinking vessels blood in the retinal fundus images has significant limitations, such as the high rate of time consumption and the possibility of human error, precisely appear with the sophisticated structure of the blood receptacle and a hung amount of the retinal fundus photograph that needs to be anatomic. Moreover, the automatic proposed algorithm that will utilize shrinking and explore helpful clinical characteristics from retinal fundus photographs in order to lead the eye caregiver to early diagnosis for various retinal disorders and therapy evaluations. A precise, quick, and fully-automatic algorithm for shrinking blood receptacles and clinical characteristics measuring technique for internal retinal pictures is suggested in order to increase the diagnostic accuracy and reduce the ophthalmologist's burden. The proposed algorithm's main pipeline consists of two fundamental stages: picture shrinkage and medical feature elicitation. Many exhaustive practices were conducted to evaluate the efficacy of the sophisticated fully-automated shrinkage system in figuring out retinal blood receptacles using the DRIVE and HRF datasets of exceedingly demanding fundus images. Initially, the accuracy of the created algorithm was tested based on its ability to accurately recognize the retinal structure of blood receptacles. In these attempts, several quantitative performance measures precisely five were computed to validate the efficacy of the exact algorithm, including accuracy (Acc.), sensitivity (Sen.), specificity (Spe.), positive prediction value (PPV), and negative prediction value (NPV). When contrast with modern receptacles shrinking approaches on the DRIVE dataset, the produced results have enormously improved by obtaining accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 98.78%, 98.32%, 97.23%, and 90. Based on five quantitative performance indicators, the HRF dataset led to the following results: 98.76%, 98.87%, 99.17%, 96.88%, and 100%. � 2022, International Journal of Advanced Computer Science and Applications. All Rights Reserved. Final 2023-05-29T09:39:18Z 2023-05-29T09:39:18Z 2022 Article 10.14569/IJACSA.2022.0131056 2-s2.0-85141789005 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141789005&doi=10.14569%2fIJACSA.2022.0131056&partnerID=40&md5=74fa75ad0ba4b08a362583ce9d4aeb21 https://irepository.uniten.edu.my/handle/123456789/27073 13 10 475 488 All Open Access, Gold Science and Information Organization Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Blood vessels; Diagnosis; Information filtering; Ophthalmology; Photography; Characteristic measurements; Clinical characteristic measurement; Clinical characteristics; Filtering algorithm; Fundus photographs; Internal picture for retinal; Manual techniques; Morphological filtering; Morphological filtering algorithm; Segmentation vessel / shrinking blood receptacle; Blood
author2 57222592694
author_facet 57222592694
Abdulsahib A.A.
Mahmoud M.A.
Al-Hasnawi S.A.
format Article
author Abdulsahib A.A.
Mahmoud M.A.
Al-Hasnawi S.A.
spellingShingle Abdulsahib A.A.
Mahmoud M.A.
Al-Hasnawi S.A.
An Algorithm for Shrinking Blood Receptacles using Retinal Internal Pictures for Clinical Characteristics Measurement
author_sort Abdulsahib A.A.
title An Algorithm for Shrinking Blood Receptacles using Retinal Internal Pictures for Clinical Characteristics Measurement
title_short An Algorithm for Shrinking Blood Receptacles using Retinal Internal Pictures for Clinical Characteristics Measurement
title_full An Algorithm for Shrinking Blood Receptacles using Retinal Internal Pictures for Clinical Characteristics Measurement
title_fullStr An Algorithm for Shrinking Blood Receptacles using Retinal Internal Pictures for Clinical Characteristics Measurement
title_full_unstemmed An Algorithm for Shrinking Blood Receptacles using Retinal Internal Pictures for Clinical Characteristics Measurement
title_sort algorithm for shrinking blood receptacles using retinal internal pictures for clinical characteristics measurement
publisher Science and Information Organization
publishDate 2023
_version_ 1806428370426134528
score 13.214268

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