Glaucoma Detection in Ultrasound biomicroscopy Images by Parametric Analysis

Biomedical image processing has experienced a dramatic expansion in research field. The processing and classification of medical images has gradually improved the resolution leading to detailed gray scale images. Along with the development of new technologies and usage of various imaging modalities the number of challenges has also increased. The present proposal proposes a novel method for detection of abnormalities in the anterior chamber of eye during the early stages of glaucoma. The increased pressure in the intraocular region can damage the optic nerve leading to a defect called glaucoma. One of the major complication
related to glaucoma is, if glaucoma is not treated on time it can cause total permanent blindness within a few
years. Ultrasound Biomicroscopy is a technique that works on the principle of ultrasonography to detect the abnormalities present in deep inner layers of the cornea. The principal objective of this project is to reduce speckle noise and categorize the statistical and morphological features. Several noise reduction filters are used for the pre-processed of UBM images. The proposed proposal aims to provide cross sectional images of anterior chamber of the eye with high resolution. The linear SVM filter being the most effective one is used to differentiate and classify the normal and glaucomatous image.