Automated Retinal Blood Vessel Feature Extraction in Digital Fundus Images-Reference-Cited by-同舟云学术

Automated Retinal Blood Vessel Feature Extraction in Digital Fundus Images

Published:2022-09-13 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)
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Author:

Nasiruddin Z. H.¹,Diyana W Zaki W Mimi¹,Hudaibah S. Assyareefah¹,Nur Asyiqin A. H²

Affiliation:

1. Universiti Kebangsaan Malaysia (UKM),Electronic and Systems Engineering, Faculty of Engineering and Built Environment,Department of Electrical,Selangor,Malaysia

2. Center for Engineering Computational Intelligence, Multimedia University,Melaka,Malaysia

Funder

Universiti Kebangsaan Malaysia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9936688/9936734/09936842.pdf?arnumber=9936842

Reference18 articles.

1. Methods for evaluation of retinal microvascular abnormalities associated with hypertension/sclerosis in the atherosclerosis risk in communities study11The authors have no proprietary interest in the equipment and techniques described in this article.

2. Fully Automatic Diameter Measurement Method Based on Retinal Vessel Segmentation

3. Retinal network characterization through fundus image processing: Significant point identification on vessel centerline

4. Revised formulas for summarizing retinal vessel diameters

5. Retinal Width Estimation of High-Resolution Fundus Images For Diabetic Retinopathy Detection

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