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Machine Learning and AI Techniques in Interactive Medical Image Analysis - Hardcover

 
9781668446713: Machine Learning and AI Techniques in Interactive Medical Image Analysis

Inhaltsangabe

The healthcare industry is predominantly moving towards affordable, accessible, and quality health care. All organizations are striving to build communication compatibility among the wide range of devices that have operated independently. Recent developments in electronic devices have boosted the research in the medical imaging field. It incorporates several medical imaging techniques and achieves an important goal for health improvement all over the world. Despite the significant advances in high-resolution medical instruments, physicians cannot always obtain the full amount of information directly from the equipment outputs, and a large amount of data cannot be easily exploited without a computer. Machine Learning and AI Techniques in Interactive Medical Image Analysis discusses how clinical efficiency can be improved by investigating the different types of intelligent techniques and systems to get more reliable and accurate diagnostic conclusions. This book further introduces segmentation techniques to locate suspicious areas in medical images and increase the segmentation accuracy. Covering topics such as computer-aided detection, intelligent techniques, and machine learning, this premier reference source is a dynamic resource for IT specialists, computer scientists, diagnosticians, imaging specialists, medical professionals, hospital administrators, medical students, medical technicians, librarians, researchers, and academicians.

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Über die Autorinnen und Autoren

Dr. Lipismita Panigrahi is from Odisha and is an Indian by birth. She is working as an Assistant Professor in the CSE Dept., OP Jindal University, Punjipathra, Raigard-496109, Chhattisgarh, India. She received her master’s degree with first class in computer applications from S.O.A. University, Odisha, India in 2012 and completed her Ph.D. in the Department of Computer Applications from NIT Raipur, India in 2020. She has around 9 years of teaching and research experience. Her research interests include digital image processing and analysis, data mining, AI, and machine learning. She was awarded with the Chhattisgarh Young Scientist Award-2017.

Prof. Sandeep Biswal received his Ph.D. degree in Electrical Engineering from NIT Raipur, India, in 2019 in the field of power system protection and M.Tech. in Power System Engineering from VSSUT (UCE) Burla, Odisha in 2013. Currently, he is Assistant Professor with the Department of Electrical Engineering, O P Jindal University, Raigarh (C. G.), India, where he has been since 2019. He is the active reviewer of many reputed journals like IEEE Transaction on Power Delivery, IEEE Transaction on Power System, IEEE Transaction on Circuit and System-I, IEEE Transaction on Circuit and System-II, IEEE Systems Journal, Journal of Electric Power Components and Systems, Taylor and Francis, European Transaction on Electrical Power, Electric Power System Research and many more. His research interests include power system relaying, distribution system protection and monitoring, and microgrid protection. He is an active member of IEEE, Member of IRC-IEEE MP Section India. Dr. Biswal is a recipient of the POSOCO Power System Award by POSOCO (PGCIL) India and Indian Institute of Technology Delhi, India, in 2019.

Prof. Akash Kumar Bhoi completed his B.Tech. (Biomedical Engineering) from TAT, Bhubaneswar and M.Tech (Biomedical Instrumentation) from Karunya University, Coimbatore in the years 2009 and 2011 respectively. He is pursuing a PhD in (Biomedical Signal Processing) from Sikkim Manipal University, India. He has been working as a R&D Faculty Associate & Assistant Professor in the Department of Electrical & Electronics Engineering at Sikkim Manipal Institute of Technology (SMIT), India since 2012. He is member of ISEIS & IAENG, Associate member of UACEE and Editorial Board member of IJAEEE, IJAEEE, ITSI-TEEE, IJECCE & IJCTT and Regular reviewer of IJET, IJCT, IJBSE, IJMI, and AJBLS & Journals of repute namely IEEE, Springer, Elsevier, Taylor & Francis etc. His areas of research are biomedical signal processing, medical image processing, sensors & transducers, and medical instrumentation. He has published several papers in national and international journals and conferences. He has also organized international conferences and workshops.

Prof. Akhtar Kalam has been at Victoria University, Melbourne since 1985 and is currently the Head of Engineering and the Chair of the Academic Board and lectures in the Masters by coursework program at Engineering Institute of Technology, Perth, Australia. Further, he has a distinguished professorship position at the University of New South Wales, Sydney, and 5 Malaysian universities. He received his B.Sc. and B.Sc. Engineering from Calcutta University and Aligarh Muslim University, India. He completed his M.S. and Ph.D. at the University of Oklahoma, USA, and the University of Bath, UK. He has been recognized internationally and nationally for his research. He is the first person to have received the John Madsen Medal from Engineers Australia in consecutive years 2016, 2019 and 2020. The John Madsen Medal is awarded for the best paper in Australia written by a current member of Engineers Australia and published in The Australian Journal of Electrical and Electronic Engineering. His outstanding impact has most recently been highlighted by his prestigious ‘ACPE-CIGRE Outstanding Academic Award (2021) win. The award recognises an exceptional Australasian academic for outstanding career-long contributions to industry, teaching and research in electric power engineering. His areas of interest are power system analysis, communication, control, protection, renewable energy, smart grid, IEC61850 implementation, and cogeneration systems. He has conducted research, provided industrial consultancy, published over six hundred publications on his area of expertise, and written over 29 books in the area. More than 48 higher degree research students have graduated under his supervision, and he is an external examiner of many external doctoral students in Australia and overseas. He provides consultancy for major electrical utilities, manufacturers, and other industry bodies in his field of expertise. Professor Kalam is a registered Professional Engineer in the state of Victoria (PEV), Fellow of EA, IET, AIE, a l if e S e n i or M ember of IEEE, NER, APEC Engineer, IntPE (Aus) and a member of CIGRE AP B5 Study Committee.

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9781668446751: Machine Learning and AI Techniques in Interactive Medical Image Analysis (Advances in Medical Technologies and Clinical Practice)

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ISBN 10:  1668446758 ISBN 13:  9781668446751
Verlag: Medical Information Science Refe..., 2022
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Buch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The healthcare industry is predominantly moving towards affordable, accessible, and quality health care. All organizations are striving to build communication compatibility among the wide range of devices that have operated independently. Recent developments in electronic devices have boosted the research in the medical imaging field. It incorporates several medical imaging techniques and achieves an important goal for health improvement all over the world. Despite the significant advances in high-resolution medical instruments, physicians cannot always obtain the full amount of information directly from the equipment outputs, and a large amount of data cannot be easily exploited without a computer. Machine Learning and AI Techniques in Interactive Medical Image Analysis discusses how clinical efficiency can be improved by investigating the different types of intelligent techniques and systems to get more reliable and accurate diagnostic conclusions. This book further introduces segmentation techniques to locate suspicious areas in medical images and increase the segmentation accuracy. Covering topics such as computer-aided detection, intelligent techniques, and machine learning, this premier reference source is a dynamic resource for IT specialists, computer scientists, diagnosticians, imaging specialists, medical professionals, hospital administrators, medical students, medical technicians, librarians, researchers, and academicians. Bestandsnummer des Verkäufers 9781668446713

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