New feature-based detection of blood vessels and exudates in color fundus images

Youssef, Doaa; Solouma, Nahed H.; El-Dib, A.F.; Mabrouk, Mai S.; Youssef, A.-B.M.

doi:10.1109/ipta.2010.5586752

Cited by 31 publications

(15 citation statements)

References 8 publications

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“…Youssef et al [12] proposed a method to detect all areas of yellow colour, the highest intensities, high contrast and the contours. Firstly, the optic disc and vessels were eliminated from the image obtained from edge detection, which gave primary estimation of the exudate regions.…”

Section: Exudates Optic Discmentioning

confidence: 99%

See 1 more Smart Citation

An intelligent mobile-based automatic diagnostic system to identify retinal diseases using mathematical morphological operations

Omar

Hossain

Zhang

et al. 2014

The 8th International Conference on Software, Knowledge, Information Management and Applications (SKIMA 2014)

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Northumbria University has developed Northumbria Research Link (NRL) to enable users to access the University's research output. Copyright © and moral rights for items on NRL are retained by the individual author(s) and/or other copyright owners. Single copies of full items can be reproduced, displayed or performed, and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided the authors, title and full bibliographic details are given, as well as a hyperlink and/or URL to the original metadata page. The content must not be changed in any way. Full items must not be sold commercially in any format or medium without formal permission of the copyright holder. The full policy is available online: http://nrl.northumbria.ac.uk/policies.html This document may differ from the final, published version of the research and has been made available online in accordance with publisher policies. To read and/or cite from the published version of the research, please visit the publisher's website (a subscription may be required.) Abstract-Diabetic retinopathy is considered in terms of the presence of exudates which cause vision loss in the areas affected. This study targets the development of an intelligent mobile-based automatic diagnosis integrated with a microscopic lens to identify retinal diseases at initial stage at any time or place. Exudate detection is a significant step in order obtaining an early diagnosis of diabetic retinopathy, and if they are segmented accurately, laser treatment can be applied effectively. Consequently, precise segmentation is the fundamental step in exudate extraction. This paper proposes a technique for exudate segmentation in colour retinal images using morphological operations. In this method, after pre-processing, the optic disc and blood vessels are isolated from the retinal image. Exudates are then segmented by a combination of morphological operations such as the modified regionprops function and a reconstruction technique. The proposed technique is verified against the DIARETDB1 database and achieves 85.39% sensitivity. The proposed technique achieves better exudate detection results in terms of sensitivity than other recent methods reported in the literature. In future work, our system will be deployed to a mobile platform to allow efficient and instant diagnosis.

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Section: Exudates Optic Discmentioning

confidence: 99%

“…Although the techniques previously presented [11][12][13][14] have provided methods to identify exudates, the authors did not clearly state how the optic disc is eliminated when in different locations. In our contrast, suggested method indicates how optic discs are isolated in different locations.…”

Section: Exudates Optic Discmentioning

confidence: 99%

An intelligent mobile-based automatic diagnostic system to identify retinal diseases using mathematical morphological operations

Omar

Hossain

Zhang

et al. 2014

The 8th International Conference on Software, Knowledge, Information Management and Applications (SKIMA 2014)

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“…Sensitivity, Specificity, positive predictive value (PPV) , positive likelihood ratio (PLR) and accuracy were used to evaluate the overall performance of the system. Doaa Youssef et al [5] proposed a method to detect the exudates using segmentation process. Firstly, the optic disc and blood vessels are eliminated.…”

Section: State Of Artmentioning

confidence: 99%

An Early Screening System for the Detection of Diabetic Retinopathy using Image Processing

Brindha¹,

Prabhakar²

2013

IJCA

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Diabetic Retinopathy (DR) is a leading cause of vision loss. Exudates are one of the significant signs of diabetic retinopathy which is a main cause of blindness that could be prevented with an early screening process In our method, the knowledge of digital image processing is used to diagnose exudates from images of retina. An automatic system to detect and localize the presence of exudates from color fundus images with non-dilated pupils is proposed. First, the image is preprocessed and segmented using CIE Lab color space. The segmented image along with Optic Disc (OD) is chosen. Feature vector based on color and texture are extracted from the selected segment using GLCM . The selected feature vector are then classified as exudates and non-exudates using a K-Nearest Neighbors Classifier. Using a clinical reference model, images with exudates were detected with 97% success rate. The proposed method performs best by segmenting even smaller area of exudates.

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“…Morfologi transformasi Top-Hat juga dapat digunakan untuk peningkatan kontras pembuluh darah [17,20,25,26,27]. Salah satu kelemahan dari metode Top-Hat adalah ketidakmampuan dalam melakukan segmentasi pembuluh darah yang kecil dan tipis [28].…”

Section: Peningkatan Kontrasunclassified

“…Selanjutnya dilakukan operasi closing dan menghasilkan sebuah citra yang menonjolkan pada daerah gelap. Pengurangan dua hasil dari morfologi tersebut akan menghasilkan citra yang telah mengalami peningkatan kontras [25].…”

Section: Peningkatan Kontrasunclassified

Review Algoritma Segmentasi Pembuluh Darah Pada Citra Fundus Retina Mata Untuk Membantu Diagnosis Diabetic Retinopathy

Putra¹,

Tjandrasa²,

Suciati³

2012

JUTI

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ABSTRAKKata Kunci: diabetic retinopathy, citra fundus retina, pembuluh darah. PENDAHULUANDiabetic Retinopathy merupakan salah satu penyakit pada retina mata yang disebabkan oleh diabetes. Penyakit ini menyebabkan keabnormalan pada retina, dan dalam kondisi terparah akan menyebabkan kebutaan. Beberapa faktor yang menyebabkan diabetic retinopathy antara lain durasi terkena penyakit diabetes, umur, tingkat tekanan darah, masa puber, kehamilan dan lain-lain [1].Durasi waktu dari penderita diabetes adalah faktor resiko terpenting dari penyakit ini. Dalam pasien yang didiagnosa mengidap penyakit diabetes sebelum usia 30 tahun, peluang munculnya diabetic retinopathy sekitar 50% setelah 10 tahun dan 90% setelah 30 tahun. Diabetic retinopathy jarang berkembang setelah 5 tahun dari serangan diabetes atau sebelum masa puber. Sekitar 5% dari diabetes tipe 2 juga mengidap diabetic retinopathy [2]. Gambar 1 merupakan pembuluh darah yang tampak dalam citra fundus retina mata.. Gambar 2 merupakan struktur anatomi dari retina mata. Dari Gambar 2 dapat terlihat, bagian-bagian dari retina mata (pembuluh darah, optic disc, dan macula) termasuk gejala-gejala dari penyakit diabetic retinopathy (exudates dan hemorrhage).Pembuluh darah merupakan salah satu faktor penting dalam pendeteksian penyakit diabetic retinopathy. Pada dasarnya kelainan pada retina mata yang disebabkan oleh penyakit diabetic retinopathy merupakan kelainan-kelainan yang ada pada pembuluh darah retina mata [3,4]. Salah satu contoh gejala diabetic retinopathy yang dapat dilihat dari pembuluh darah antara lain munculnya microaneurysm dan hemorrhage yang disebabkan adanya tonjolan yang ada pada pembuluh darah dalam retina mata [5]. Oleh karena itu diperlukannya suatu metode untuk segmentasi pembuluh darah yang tepat dan baik agar tonjolan yang ada pada pembuluh darah dalam retina dapat terdeteksi secara jelas.Berbagai penelitian mengenai segmentasi pembuluh darah telah dilakukan oleh beberapa peneliti dalam beberapa tahun terakhir. Beberapa makalah yang digunakan sebagai acuan dalam penelitian ini terlihat pada Gambar 3. Dari Gambar 3 terlihat bahwa makalah yang terbanyak dipakai dalam penelitian ini adalah makalah yang dipublikasikan pada tahun 2012. Makalah ini berjumlah 12, merupakan 23% dari jumlah makalah yang dipakai dalam penelitian ini. Hasil penelitian mereka dapat disimpulkan bahwa pada dasarnya metode untuk segmentasi pembuluh darah pada citra fundus retina mata terdiri dari 3 tahap, yakni: preprocessing, segmentasi dan postprocessing.Makalah ini disusun sebagai berikut. Pada bagian pertama dijelaskan mengenai segmentasi pembuluh darah pada diabetic retinopathy. Pada bagian kedua dijelaskan mengenai preprocessing yang digunakan dalam algoritma segmentasi pembuluh darah. Pada bagian ketiga dijelaskan mengenai proses segmentasi yang digunakan. Proses segmentasi ini terbagi menjadi tiga, yakni image based, pattern recognition based dan vessel tracking/tracing. Pada bagian keempat dijelaskan

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New feature-based detection of blood vessels and exudates in color fundus images

Cited by 31 publications

References 8 publications

An intelligent mobile-based automatic diagnostic system to identify retinal diseases using mathematical morphological operations

An intelligent mobile-based automatic diagnostic system to identify retinal diseases using mathematical morphological operations

An Early Screening System for the Detection of Diabetic Retinopathy using Image Processing

Review Algoritma Segmentasi Pembuluh Darah Pada Citra Fundus Retina Mata Untuk Membantu Diagnosis Diabetic Retinopathy

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