Techniques of Image Processing and Segmentation in Predicting Hydrocephalus using Magnetic Resonance Image

Abstract

Children are most commonly affected by many neurological disorders now a days. One of the common disease is hydrocephalus occurring 1/1000 in infantile age group and also in adults as a result of congenital, acquired, tumors, spina bifida, bleeding or infection. Hydrocephalus may cause disability and even death when it is left untreated. Hydrocephalus occurs when, due to previous causes in the brain, excessive cerebrospinal fluid builds up in the brain. When diagnosing tumours and hydrocephalus, image processing plays a vital role. The gap between the visual representation of data captured by MRI and the information relevant to the individual is a major challenge in the medical field. The latest image processing and data mining technologies are used to classify images with high precision. This research paper suggest a definition of image processing and segmentation algorithms for the evaluation of hydrocephalus in children and the determination of its MRI volume. Earlier research work are intended for identifying Hydrocephalus from CT brain images. But in the proposed work MRI images are used for diagnosis. This paper presents techniques and algorithms of Image processing and Segmentation which will be very useful in diagnosing Hydrocephalus.