Magnetic Resonance Imaging

Professor V. Rajinikanth works in the Department of Electronics and Instrumentation Engineering at St. Joseph’s College of Engineering in Chennai, Tamilnadu, India. Nilanjan Dey (Senior Member, IEEE) received the B.Tech., M.Tech. in information technology from West Bengal Board of Technical University and Ph.D. degrees in electronics and telecommunication engineering from Jadavpur University, Kolkata, India, in 2005, 2011, and 2015, respectively. Currently, he is Associate Professor with the Techno International New Town, Kolkata and a visiting fellow of the University of Reading, UK. He has authored over 300 research articles in peer-reviewed journals and international conferences and 40 authored books. His research interests include medical imaging and machine learning. Moreover, he actively participates in program and organizing committees for prestigious international conferences, including World Conference on Smart Trends in Systems Security and Sustainability (WorldS4), International Congress on Information and Communication Technology (ICICT), International Conference on Information and Communications Technology for Sustainable Development (ICT4SD) etc. He is also the Editor-in-Chief of International Journal of Ambient Computing and Intelligence, Associate Editor of IEEE Transactions on Technology and Society and series Co-Editor of Springer Tracts in Nature-Inspired Computing and Data-Intensive Research from Springer Nature and Advances in Ubiquitous Sensing Applications for Healthcare from Elsevier etc. Furthermore, he was an Editorial Board Member Complex & Intelligence Systems, Springer, Applied Soft Computing, Elsevier and he is an International Journal of Information Technology, Springer, International Journal of Information and Decision Sciences etc. He is a Fellow of IETE and member of IE, ISOC etc.

1. Introduction to Image Assisted Disease Screening 2. Magnetic Resonance Imaging – Recording and Reconstruction 3. Image Processing Schemes to Enhance Disease Information in MRI Slices 4. Segmentation of Tumor in Breast MRI Using Entropy Thresholding and Mayfly-Algorithm: A Study 5. Abnormality Detection in Heart MRI with Spotted-Hyena-Algorithm Supported Kapur/Otsu Thresholding and Level-Set Segmentation 6. CNN based Segmentation of Brain Tumor from T2-Weighted MRI Slices 7. Automated Detection of Ischemic-Stroke with Brain MRI using Machine-Learning and Deep-Learning Features