Siddhartha Bhattacharyya

Sambhunath Biswas

Debanjan Konar

Mousumi Gupta

This book includes high-quality papers presented at the Symposium 2019, organised by Sikkim Manipal Institute of Technology (SMIT), in Sikkim from 26–27 February 2019. It discusses common research problems and challenges in medical image analysis, such as deep learning methods. It also discusses how these theories can be applied to a broad range of application areas, including lung and chest x-ray, breast CAD, microscopy and pathology. The studies included mainly focus on the detection of events from biomedical signals.

International Symposium, ISCMM 2019

Computer Vision and Machine Intelligence in Medical Image Analysis

Kalpana Sharma

Tapan Kumar Gandhi

Biswaraj Sen

This book presents high-quality, peer-reviewed papers from the Third International Conference on Advanced Computational and Communication Paradigms (ICACCP 2021), organized by Department of Computer Science and Engineering (CSE), Sikkim Manipal Institute of Technology (SMIT), Sikkim, India during 22 – 24 March 2021. ICACCP 2021 covers an advanced computational paradigms and communications technique which provides failsafe and robust solutions to the emerging problems faced by mankind. Technologists, scientists, industry professionals and research scholars from regional, national and international levels are invited to present their original unpublished work in this conference.

Proceedings of ICACCP 2021

Advanced Computational Paradigms and Hybrid Intelligent Computing

Jan Platos

Chinmoy Kar

The book discusses the impact of machine learning and computational intelligent algorithms on medical image data processing, and introduces the latest trends in machine learning technologies and computational intelligence for intelligent medical image analysis. The topics covered include automated region of interest detection of magnetic resonance images based on center of gravity; brain tumor detection through low-level features detection; automatic MRI image segmentation for brain tumor detection using the multi-level sigmoid activation function; and computer-aided detection of mammographic lesions using convolutional neural networks.

Hybrid Machine Intelligence for Medical Image Analysis

Debanjan Konar

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