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PROJECT TITLE :

Difference image and fuzzy c-means for detection Of retinal vessels - 2016

ABSTRACT:

Digital retinal photography and the application of computer vision in ophthalmology are increasingly turning into helpful in the diagnosis and management of retinopathies and cardiovascular diseases. Although many automatic methods of detecting vessels in retinal images have been proposed, there has but been a would like for improved automatic vessel detection ways that is capable of handling the problem of enormous vessel network connectivity and poor detection of thin retinal vessels. A study that mixes difference image (DI) with fuzzy c-means that (FCM) for the detection of vessels in retinal images is presented during this paper. The DI is employed to handle noise caused by illumination variation within the pre-processing of retinal pictures and therefore the vessels are detected using FCM. A post-processing part that mixes completely different morphological operations for the removal of the noisy pixels was applied. The method proposed in this paper achieves a high average sensitivity rate of zero.7302 and average accuracy rate of zero.944four on DRIVE database. In comparison with several previously proposed ways in the literature, the method proposed during this paper achieves promising results.


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Image Denoising Medical Image Processing Blood Vessels Object Detection Lighting Retinal Recognition Retinal Vessels Detection Difference Image Fuzzy C-Means
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