Dissertation/Thesis Abstract

A Multi-Anatomical Retinal Structure Segmentation System for Automatic Eye Screening Using Morphological Adaptive Fuzzy Thresholding
by Almotiri, Jasem, Ph.D., University of Bridgeport, 2018, 138; 10975223
Abstract (Summary)

Eye exam can be as efficacious as physical one in determining health concerns. Retina screening can be the very first clue to detecting a variety of hidden health issues including pre-diabetes and diabetes. Through the process of clinical diagnosis and prognosis; ophthalmologists rely heavily on the binary segmented version of retina fundus image; where the accuracy of segmented vessels, optic disc and abnormal lesions extremely affects the diagnosis accuracy which in turn affect the subsequent clinical treatment steps. This thesis proposes an automated retinal fundus image segmentation system composed of three segmentation subsystems follow same core segmentation algorithm. Despite of broad difference in features and characteristics; retinal vessels, optic disc and exudate lesions are extracted by each subsystem without the need for texture analysis or synthesis. For sake of compact diagnosis and complete clinical insight, our proposed system can detect these anatomical structures in one session with high accuracy even in pathological retina images.

The proposed system uses a robust hybrid segmentation algorithm combines adaptive fuzzy thresholding and mathematical morphology. The proposed system is validated using four benchmark datasets: DRIVE and STARE (vessels), DRISHTI-GS (optic disc), and DIARETDB1 (exudates lesions). Competitive segmentation performance is achieved, outperforming a variety of up-to-date systems and demonstrating the capacity to deal with other heterogenous anatomical structures.

Indexing (document details)
Advisor: Elleithy, Khaled M.
Commitee: Faezipour, Miad, Gupta, Navarun, Rizvi, Syed, Xiong, Xingguo
School: University of Bridgeport
Department: Computer Science and Engineering
School Location: United States -- Connecticut
Source: DAI-B 80/03(E), Dissertation Abstracts International
Source Type: DISSERTATION
Subjects: Computer Engineering, Medical imaging, Computer science
Keywords: Fuzzy systems, Image segmentation, Optic disc segmentation, Retina screening, Retinal exudate segmentation, Retinal vessels segmentation
Publication Number: 10975223
ISBN: 9780438575455
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