Medical Imaging Informatics

Medical Imaging Informatics is an edited book that discusses how medical images can be processed using machine learning techniques and big data analysis methods. These tools help physicians to gain a full overview of a patient's data, which in turn assists with diagnosis, prognosis or intervention. 

Mamoon Rashid is currently working as an associate professor in the Department of Computer Engineering, Faculty of Science and Technology, Vishwakarma University, Pune, India. He also holds a position of director, Research Center of Excellence for Health Informatics, Vishwakarma University, Pune, India. He received his Ph.D. from the Department of Computer Science and Engineering, Punjabi University, Patiala, India, in the field of Medical Imaging Informatics. He has published 100+ papers indexed in SCI/SCIE journals and conferences of international repute. He also edited a book titled Artificial Intelligence for Innovative Healthcare Informatics, Springer, in 2022. He served as a lead guest editor for many journals indexing in Web of Science. His research interests include health informatic, medical imaging, and image processing.

Vishal Goyal is a full professor in the Department of Computer Science, Punjabi University Patiala, India, with teaching and research experience of 21+ years. He is also holding positions of co-coordinator for "Center for Artificial Intelligence and Data Science," coordinator for "Research Centre for technology Development for Differently Abled Persons," and director of the Centre for E-Learning and Teaching Excellence, Punjabi University, India. He is an approved consultant for AIU in consulting universities and colleges for accreditation rankings of NAAC, NIRF, NBA, and international linkages. He has been awarded the Young Scientist Award in 2015 by the Punjab Academy of Sciences, and two times State Award by the Government of Punjab, India. He has published 100+ research publications in various journals and conferences of national and international repute. He completed his grant projects with 10 million Indian rupees funded by various ministries of Govt. of India and has a number of projects in progress. His research areas are natural language processing, technology development for differently abled people, and machine learning.

Ali Kashif Bashir is a reader in the Department of Computing and Mathematics, Manchester Metropolitan University, UK. He is the leader of Future Networks Lab and head of Advanced Cybersecurity Testbed. He is supervising/co-supervising a number of Ph.D. students, Postdocs, and research associates. Along with his students and colleagues, he has published over 250 high-impact articles in top venues. He has obtained over £4 million external funding from UK, South Korean, Japanese, European, Asian, and Middle Eastern agencies. He is also Co-I of GM AI and GM Cyber Foundry, each having £6 million funding. He is a senior member of IEEE, a member of 10+ IEEE technical societies, and a distinguished speaker of ACM. He has chaired several international conferences and workshops and has delivered over 40 invited and keynote talks across the globe. He also enjoys several honorary and adjunct professor positions in many countries like China, Canada, Lebanon, UAE, India, and Pakistan. He is serving as an editor-in-chief of IEEE Technology, Policy and Ethics and Journal of Autonomous Intelligence, and an editor of over 10 international journals including Scientific Reports, Nature, and IEEE Transactions on Network Science and Engineering.

Saqib Hakak is an assistant professor at the Canadian Institute for Cybersecurity, University of New Brunswick, Canada. He has 6+ years of industrial and academic experience. He has received a number of Gold/Silver awards in international innovation competitions and is serving as a technical committee member/reviewer of several reputed conference/journal venues. He has published 90+ papers in journals of repute. His research interests include risk management, fake news detection using AI, security and privacy concerns in IoE, applications of federated learning in IoT, and blockchain technology.