Detection and Grading of Hypertensive Retinopathy Using Vessels Tortuosity and Arteriovenous Ratio.
Hypertensive retinopathy (HR) refers to changes in the morphological diameter of the retinal vessels due to persistent high blood pressure. Early detection of such changes helps in preventing blindness or even death due to stroke. These changes can be quantified by computing the arteriovenous ratio...
| Publicado en: | Journal of Digital Imaging Vol. 35; no. 2; pp. 281 - 302 |
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| Autores principales: | , , , , , , |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Apr2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=155757665&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 155757665 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Apr2022 vid: 35 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 155757665 154589390 155757665 155757665 10.1007/s10278-021-00545-z 155757665 ppf: 281 ppct: 21 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Detection and Grading of Hypertensive Retinopathy Using Vessels Tortuosity and Arteriovenous Ratio. aug: au: Badawi, Sufian A. Fraz, Muhammad Moazam Shehzad, Muhammad Mahmood, Imran Javed, Sajid Mosalam, Emad Nileshwar, Ajay Kamath affil: School of Electrical Engineering and Computer Science, National University of Sciences and Technology (NUST), Islamabad, Pakistan sug: subj: Hypertension Diagnosis Retinal Diseases Diagnosis Retinal Vein Analysis Retinal Artery Analysis Severity of Illness Evaluation Diagnosis, Computer Assisted Decision Support Systems, Clinical Human Automation Intraocular Pressure Descriptive Statistics Image Interpretation, Computer Assisted Image Processing, Computer Assisted ab: Hypertensive retinopathy (HR) refers to changes in the morphological diameter of the retinal vessels due to persistent high blood pressure. Early detection of such changes helps in preventing blindness or even death due to stroke. These changes can be quantified by computing the arteriovenous ratio and the tortuosity severity in the retinal vasculature. This paper presents a decision support system for detecting and grading HR using morphometric analysis of retinal vasculature, particularly measuring the arteriovenous ratio (AVR) and retinal vessel tortuosity. In the first step, the retinal blood vessels are segmented and classified as arteries and veins. Then, the width of arteries and veins is measured within the region of interest around the optic disk. Next, a new iterative method is proposed to compute the AVR from the caliber measurements of arteries and veins using Parr–Hubbard and Knudtson methods. Moreover, the retinal vessel tortuosity severity index is computed for each image using 14 tortuosity severity metrics. In the end, a hybrid decision support system is proposed for the detection and grading of HR using AVR and tortuosity severity index. Furthermore, we present a new publicly available retinal vessel morphometry (RVM) dataset to evaluate the proposed methodology. The RVM dataset contains 504 retinal images with pixel-level annotations for vessel segmentation, artery/vein classification, and optic disk localization. The image-level labels for vessel tortuosity index and HR grade are also available. The proposed methods of iterative AVR measurement, tortuosity index, and HR grading are evaluated using the new RVM dataset. The results indicate that the proposed method gives superior performance than existing methods. The presented methodology is a novel advancement in automated detection and grading of HR, which can potentially be used as a clinical decision support system. pubtype: Academic Journal doctype: diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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