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- 实验方案
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Automatic optic disc localization and segmentation in retinal images by a line operator and level sets
摘要： BACKGROUND: Existing methods may fail to locate and segment the optic disc (OD) due to imprecise boundaries, inconsistent image contrast and deceptive edge features in retinal images. OBJECTIVE: To locate the OD and detect the OD boundary accurately. METHODS: The method exploits a multi-stage strategy in the detection procedure. Firstly, OD location candidate regions are identi?ed based on high-intensity feature and vessels convergence property. Secondly, a line operator ?lter for circular brightness feature detection is designed to locate the OD accurately on candidates. Thirdly, an initialized contour is obtained by iterative thresholding and ellipse ?tting based on the detected OD position. Finally, a region-based active contour model in a variational level set formulation and ellipse ?tting are employed to estimate the OD boundary. RESULTS: The proposed methodology achieves an accuracy of 98.67% for OD identi?cation and a mean distance to the closest point of 2 pixels in detecting the OD boundary. CONCLUSION: The results illuminate that the proposed method is effective in the fast, automatic, and accurate localization and boundary detection of the OD. The present work contributes to the more effective evaluation of the OD and realizing automatic screening system for early eye diseases to a large extent.
关键词： optic disc segmentation,level set method,retinal images,Optic disc localization
更新于2025-09-23 15:22:29
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[IEEE 2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC) - Mon Tresor, Plaine Magnien, Mauritius (2018.12.6-2018.12.7)] 2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC) - Optic Disc Segmentation Based on Correlation Feature Information
摘要： Glaucoma, one of the major causes of blindness, has been identified as a disease that causes the degeneration of the optic disc. An highly accurate automated detection of the optic disc (OD) has however been noted to be of great importance for the efficient diagnosis of the disease. This paper presents a study on an unsupervised approach usage of Haralick Correlation texture feature for the segmentation of optic disc in colored fundus retinal images. The grayscale and green channel of the colored fundus image are investigated. When compared with some methods in the literature, the experimental study of the proposed method achieved very high average accuracy rates of 98.59% and 98.36% using grayscale and green channel of the colored fundus image respectively on DRIVE database.
关键词： Optic disc,Segmentation,Correlation,Haralick Feature,image processing,Glaucoma
更新于2025-09-23 15:22:29
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Segmentation and Classification of Optic Disc in Retinal Images
摘要： Image segmentation plays a vital role in image analysis for diagnosis of various retinopathy diseases. For the detection of glaucoma and diabetic retinopathy, manual examination of the optic disc is the standard clinical procedure. The proposed method makes use of the circular transform to automatically locate and extract the Optic Disc (OD) from the retinal fundus images. The circular transform operates with radial line operator which uses the multiple radial line segments on every pixel of the image. The maximum variation pixels along each radial line segments are taken to detect and segment OD. The input retinal images are preprocessed before applying circular transform. The optic disc diameter and the distance from optic disc to macula are found for a sample of 20 images. An Extreme Learning Machine classifier is used to train the neural network to classify the images as normal or abnormal. Its performance is compared with Support Vector Machine in terms of computation time and accuracy. It is found that computation time is less than 0.1 sec and accuracy is 97.14% for Extreme Learning Machine classifier.
关键词： extreme learning machine,Circular transform,optic disc,segmentation,macula
更新于2025-09-09 09:28:46