An Automated Graphical User Interface based System for the Extraction of Retinal Blood Vessels using Kirsch’s Template
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2015, Vol 6, Issue 6
Abstract
The assessment of Blood Vessel networks plays an important role in a variety of medical disorders. The diagnosis of Diabetic Retinopathy (DR) and its repercussions including micro aneurysms, haemorrhages, hard exudates and cotton wool spots is one such field. This study aims to develop an automated system for the extraction of blood vessels from retinal images by employing Kirsch’s Templates in a MATLAB based Graphical User Interface (GUI). Here, a RGB or Grey image of the retina (Fundus Photography) is used to obtain the traces of blood vessels. We have incorporated a range of Threshold values for the blood vessel extraction which would provide the user with greater flexibility and ease. This paper also deals with the more generalized implementation of various MATLAB functions present in the image processing toolbox of MATLAB to create a basic image processing editor with different features like noise addition and removal, image cropping, resizing & rotation, histogram adjust, separately viewing the red, green and blue components of a colour image along with brightness control, that are used in a basic image editor. We have combined both Kirsch’s Template and various MATLAB Algorithms to obtain enhanced images which would allow the ophthalmologist to edit and intensify the images as per his/her requirement for diagnosis. Even a non technical person can manage to identify severe discrepancies because of its user friendly appearance. The GUI contains very commonly used English Language viz. Load, Colour Contrast Panel, Image Clarity etc that can be very easily understood. It is an attempt to incorporate maximum number of image processing techniques under one GUI to obtain higher performance. Also it would provide a cost effective solution towards obtaining high definition and resolution images of blood vessel extracted Retina in economically backward regions where costly machine like OCT (Optical Coherence Tomography), MRI (Magnetic Resonance Imaging) are not available. Hence an early detection of irregularity will be possible especially in rural areas.
Authors and Affiliations
Joshita Majumdar, Souvik Tewary, Shreyosi Chakraborty, Debasish Kundu, Sudipta Ghosh, Sauvik Gupta
Keywords
Related Articles
- EP ID EP127453
- DOI 10.14569/IJACSA.2015.060613
- Views 99
- Downloads 0
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