Advanced Machine Vision Paradigms for Medical Image Analysis
97,99 €
inkl. MwSt.
Versandkostenfrei*
Versandfertig in 6-10 Tagen
payback
49 °P sammeln
  • Broschiertes Buch

Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of…mehr

Andere Kunden interessierten sich auch für
Produktbeschreibung
Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated.

Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs.
Autorenporträt
Dr Tapan K Gandhi is currently working as Associate Professor in the Dept. of Electrical Engineering, IIT Delhi and adjunct faculty in the school of AI and data science, IIT Jodhpur. He is also a research affiliate at MIT, USA. He received his Ph.D. fellowship from (MIT, USA) and obtained his Ph.D. in Biomedical Engineering from IIT Delhi. He has published papers in top ranking journals and has more than 150 publications in international journals and conference proceedings. He is PI & Co-PI of many funded projects from Industry, International Organizations as well as Govt. of India organizations.

Dr. Sourav De completed his PhD in Computer Science and Technology at the Indian Institute of Engineering & Technology, Shibpur, Howrah, India in 2015. He is currently an Associate Professor of Computer Science & Engineering at Cooch Behar Government Engineering College, West Bengal. He is a co-author of one book, the co-editor of twelve books, and has more than 54 research publications in internationally reputed journals, international edited books, international IEEE conference proceedings, and one patent to his credit. His research interests include soft computing, pattern recognition, image processing, and data mining. Dr. De is a senior member of IEEE and a member of ACM, Institute of Engineers (IEI), Computer Science Teachers Association (CSTA), Institute of Engineers and IAENG, Hong Kong. He is a life member of ISTE, India.