A Multi-Anatomical Retinal Structure Segmentation System for Automatic Eye Screening Using Morphological Adaptive Fuzzy Thresholding
| العنوان: | A Multi-Anatomical Retinal Structure Segmentation System for Automatic Eye Screening Using Morphological Adaptive Fuzzy Thresholding |
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| المؤلفون: | Abdelrahman Elleithy, Khaled M. Elleithy, Jasem Almotiri |
| المصدر: | IEEE Journal of Translational Engineering in Health and Medicine, Vol 6, Pp 1-23 (2018) IEEE Journal of Translational Engineering in Health and Medicine |
| بيانات النشر: | IEEE, 2018. |
| سنة النشر: | 2018 |
| مصطلحات موضوعية: | lcsh:Medical technology, genetic structures, Computer science, Biomedical Engineering, morphological operations, optic disc segmentation, 02 engineering and technology, Mathematical morphology, lcsh:Computer applications to medicine. Medical informatics, Fuzzy logic, Article, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, adaptive local thresholding, retinopathy, 0202 electrical engineering, electronic engineering, information engineering, medicine, Segmentation, fuzzy C-means, retinal exudate segmentation, Retina, business.industry, Retina screening, Pattern recognition, General Medicine, Fuzzy control system, Image segmentation, Thresholding, eye diseases, retinal vessels segmentation, medicine.anatomical_structure, lcsh:R855-855.5, fuzzy systems, lcsh:R858-859.7, 020201 artificial intelligence & image processing, Artificial intelligence, business, Optic disc |
| الوصف: | Eye exam can be as efficacious as physical one in determining health concerns. Retina screening can be the very first clue for 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 paper 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 heterogeneous anatomical structures. |
| اللغة: | English |
| تدمد: | 2168-2372 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::34d8354ccff5330704523ac2221f55be https://ieeexplore.ieee.org/document/8360472/ |
| Rights: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....34d8354ccff5330704523ac2221f55be |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 21682372 |
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