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Kanakaraj, S, V.K G, P.N P.  2012.  A Fast Brain Image Registration Using Axial Transformation. Wireless Networks and Computational Intelligence Communications in Computer and Information Science. 292:206-212.
Kanakaraj, S, GovindanV.K., P.N. P.  2012.  A Fast Brain Image Registration Using Axial Transformation. Wireless Networks and Computational Intelligence. (Venugopal, K. R., Patnaik, L. M., Eds.).:206–212., Berlin, Heidelberg: Springer Berlin Heidelberg Abstract

The registration process in the medical field has evolved rapidly making the physicians to rely on computer algorithms for processing and diagnosing the diseases. Registration has been used for studying disease growth and treatment responses of the diseases. Brain image registration enables physicians to diagnose diseases like Alzheimer's based on the changes in the internal structure of the brain. One of the main challenges in this topic is the huge computational requirements of the registration processes. In this paper we propose a method for the fast and accurate registration of MR brain images using the shape property of the axial slice of the brain. The algorithm exhibits reduced computational time when compared to a standard existing approach, which makes it useful for real time applications.

Kaur, G, Joseph AJ, N PP.  2022.  Patch-based All Convolutional Neural Network Model for Classification of Benign and Malignant Mammograms. 2022 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES). 1:448-455. Abstract
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