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Blood Vessel Segmentation For High Resolution Retinal Images

Segmentation of blood vessels in retinal images used for the early diagnosis of retinal diseases such as hypertension, diabetes and glaucoma. The high resolution, variability in vessel width, brightness and low contrast make vessel segmentation as difficult task. There exist several methods for segmenting blood vessels from retinal images. However, most of these methods fail to segment high resolution (large in size) images, very few methods provide solution for such a high resolution images but it require lengthy elapsed time and the accuracy of these methods is not completely satisfactory. Parallel method have emerged to overcome these limitations by offering parallel environment and parallel algorithm to segment such an high resolution images in an acceptable time. The planned research enhances the speed and accuracy of segmentation for high resolution retinal images by involving a new data partition scheme and suitable segmentation algorithm for parallel environment.