Article ID Journal Published Year Pages File Type
503982 Computerized Medical Imaging and Graphics 2015 13 Pages PDF
Abstract

•We propose an adaptive vessel segmentation approach to characterize vasculature.•We apply AM-FM along with this vessel segmentation method to better capture NVD.•We characterize the entire vasculature in the optic disc to detect NVD.•This approach is validated on a large dataset and achieves good results.

This paper presents a multiscale method to detect neovascularization in the optic disc (NVD) using fundus images. Our method is applied to a manually selected region of interest (ROI) containing the optic disc. All the vessels in the ROI are segmented by adaptively combining contrast enhancement methods with a vessel segmentation technique. Textural features extracted using multiscale amplitude-modulation frequency-modulation, morphological granulometry, and fractal dimension are used. A linear SVM is used to perform the classification, which is tested by means of 10-fold cross-validation. The performance is evaluated using 300 images achieving an AUC of 0.93 with maximum accuracy of 88%.

Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
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