Description: The constantly evolving healthcare industry has experienced tremendous technological advancements that have significantly revolutionized medical imaging. However, with the increasing volume and complexity of medical image data, existing analysis methods must also be updated to be efficient and accurate. This is where the challenge lies--a need for a comprehensive solution that bridges the gap between cutting-edge technology and effective healthcare delivery. Computer-Assisted Analysis for Digital Medicinal Imagery offers a roadmap for navigating the intricate landscape of digital medicinal imagery analysis. Unlocking the power of machine learning and breaking down the basics provides researchers, clinicians, and students with the tools necessary to harness technology and improve healthcare outcomes.
Brief description: Pranshu Saxena received the B. E. in (2010), M. Tech. (2013), and PhD in 2023. He is currently an Assistant Professor in the Department of Information Technology at the ABES Engineering College, Ghaziabad, India. He has published 22 research articles which include 4-SCI, 6-Scopus, and 12 peer-review journals/conferences. His research interests include medical image processing, automated image segmentation, Image texture analysis, intelligent systems and Pattern Classification. He has been a designated reviewer (ISIEA 2012-2013, IJERT) and committee member (IJACR) for many international conferences and journals in image processing and medical imaging. He has published one book published by LAP Lambert Academic Publishing, USA.