MRI BRAIN IMAGE ENHANCEMENT USING TRANSFER LEARNING AND QUATERNION MATRIX ANALYSIS- A REVIEW

Abstract

This paper provides the information about an effective method for MRI brain image enhancement. The automatic segmentation of brain-tissue has led to the variation in the images due to different scanning and the imaging protocols which makes the image unclear and thus application is hampered. The transfer learning with weighted SVM enables training data to minimize  classification errors as the classification scheme needs only a small amount of representative data. Therefore a new optimally standardized method is presented for scanned image segmentation using Transfer Learning with Weighted Support Vector
Machine and then further improving the training data quality by Vector Sparse Representation using Iterative Algorithm for Quaternion Matrix Analysis over Reflexive Matrices.