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Open AccessArticle

A Multi-Scale Directional Line Detector for Retinal Vessel Segmentation

1
Department of Electrical and Computer Engineering, COMSATS University Islamabad (CUI), Islamabad 45550, Pakistan
2
Biometric and Sensor Lab, Effat University, Jeddah 34689, Saudi Arabia
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(22), 4949; https://doi.org/10.3390/s19224949
Received: 9 October 2019 / Revised: 2 November 2019 / Accepted: 8 November 2019 / Published: 13 November 2019
(This article belongs to the Special Issue Biomedical Imaging and Sensing)
The assessment of transformations in the retinal vascular structure has a strong potential in indicating a wide range of underlying ocular pathologies. Correctly identifying the retinal vessel map is a crucial step in disease identification, severity progression assessment, and appropriate treatment. Marking the vessels manually by a human expert is a tedious and time-consuming task, thereby reinforcing the need for automated algorithms capable of quick segmentation of retinal features and any possible anomalies. Techniques based on unsupervised learning methods utilize vessel morphology to classify vessel pixels. This study proposes a directional multi-scale line detector technique for the segmentation of retinal vessels with the prime focus on the tiny vessels that are most difficult to segment out. Constructing a directional line-detector, and using it on images having only the features oriented along the detector’s direction, significantly improves the detection accuracy of the algorithm. The finishing step involves a binarization operation, which is again directional in nature, helps in achieving further performance improvements in terms of key performance indicators. The proposed method is observed to obtain a sensitivity of 0.8043, 0.8011, and 0.7974 for the Digital Retinal Images for Vessel Extraction (DRIVE), STructured Analysis of the Retina (STARE), and Child Heart And health Study in England (CHASE_DB1) datasets, respectively. These results, along with other performance enhancements demonstrated by the conducted experimental evaluation, establish the validity and applicability of directional multi-scale line detectors as a competitive framework for retinal image segmentation. View Full-Text
Keywords: directional filter bank; image segmentation; multi-scale line detector; vessel segmentation directional filter bank; image segmentation; multi-scale line detector; vessel segmentation
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Khawaja, A.; Khan, T.M.; Khan, M.A.U.; Nawaz, S.J. A Multi-Scale Directional Line Detector for Retinal Vessel Segmentation. Sensors 2019, 19, 4949.

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