Error Detection and Correction in EG-LDPC Code using Majority Logic Design

Abstract

Abstract:

         Brain magnetic resonance segmentation and detection is a very complex problem in the field of medical imaging in spite of various present methods. MR image of brain can be possibly divided into sub regions especially soft tissues such as gray matter, white matter and CSF. Tumor segmentation and classification is an important but time consuming task if computed by human expert but if we automated this process we can reduce this time with better accuracy. The computer aided diagnosis algorithm has been designed to increase the accuracy of tumor detection and classification so as to replace the conventional time consuming techniques. The propose algorithm has been designed to detect and classify the tumor into cancerous, non-cancerous and highly cancerous with help of probabilistic neural network