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Computer Aided Intervention and Diagnostics in Clinical and Medical Images (eBook)

Artikelnummer: 978-3-030-04061-1
Einband: PDF
Verfügbarkeit: Download, sofort verfügbar (Link per E-Mail)
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This book is a compendium of the ICCMIA 2018 proceedings, which provides an ideal reference for all medical imaging researchers and professionals to explore innovative methods and analyses on imaging technologies for better prospective patient care. 

This work serves as an exclusive source for new computer assisted clinical and medical developments in imaging diagnosis, intervention and analysis. It includes articles on computer assisted medical scanning techniques, computer-aided diagnosis, robotic surgery and imaging, imaging genomics, clinically-oriented imaging physics and informatics, augmented-reality medical visualization, imaging modalities, computerized radiology, oncology, and surgery. Moreover, information on non-medical imaging that has medical applications such as multi-photon microscopy and confocal, photoacoustic imaging, optical microendoscope, infra-red radiation, and other imaging modalities is also represented.


This book is a compendium of the ICCMIA 2018 proceedings, which provides an ideal reference for all medical imaging researchers and professionals to explore innovative methods and analyses on imaging technologies for better prospective patient care. 

This work serves as an exclusive source for new computer assisted clinical and medical developments in imaging diagnosis, intervention and analysis. It includes articles on computer assisted medical scanning techniques, computer-aided diagnosis, robotic surgery and imaging, imaging genomics, clinically-oriented imaging physics and informatics, augmented-reality medical visualization, imaging modalities, computerized radiology, oncology, and surgery. Moreover, information on non-medical imaging that has medical applications such as multi-photon microscopy and confocal, photoacoustic imaging, optical microendoscope, infra-red radiation, and other imaging modalities is also represented.


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VerlagSpringer International Publishing
EinbandPDF
Erscheinungsjahr2019
Seitenangabe301 S.
AusgabekennzeichenEnglisch
AbbildungenVII, 301 p. 136 illus., 95 illus. in color.
Masse10'810 KB
PlattformPDF
ReiheLecture Notes in Computational Vision and Biomechanics; Engineering; Engineering ; Springer Nature Proceedings excluding Computer Science
AutorPeter, J. Dinesh (Hrsg.) / Fernandes, Steven Lawrence (Hrsg.) / Eduardo Thomaz, Carlos (Hrsg.) / Viriri, Serestina (Hrsg.)

Alle Bände der Reihe "Lecture Notes in Computational Vision and Biomechanics; Engineering; Engineering (R0); Springer Nature Proceedings excluding Computer Science"

Über den Autor J. Dinesh (Hrsg.) Peter

J. Dinesh Peter is currently working as an associate professor, Department of Computer Sciences Technology at Karunya University, Coimbatore. Before this, he was a full-time research scholar at the National Institute of Technology, Calicut, India, from where he received his Ph.D. in computer science and engineering. His research focus includes big data, image processing, and computer vision. He has several publications in various reputed international journals and conference papers which are widely referred to. He is a member of IEEE, CSI & IEI and has served as session chairs and delivered plenary speeches for various international conferences and workshops. Dr. Amir H. Alavi is an assistant professor in the Department of Civil and Environmental Engineering and holds a courtesy appointment in the Department of Bioengineering at the University of Pittsburgh. Dr. Alavi's research interests include structural health monitoring, multifunctional structures, advanced sensors, low-power energy harvesting, and engineering informatics. His research activities involve the implementation of self-sustained and multifunctional sensing and structural systems enhanced by engineering informatics in the fields of civil infrastructure, construction, aerospace, and biomedical engineering. Dr. Alavi has authored seven books and over 200 publications in archival journals, chapters, and conference proceedings. He has received several award certificates for his journal articles. He is among the Google Scholar 200 Most Cited Authors in Civil Engineering, Web of Science ESI's World Top 1% Scientific Minds in 2018, and the Stanford University list of Top 1% Scientists in the World 2020. Steven Fernandes is an assistant professor in the Department of Computer Science at Karunya University, Coimbatore. After earning his Ph.D. in Electronics and Communication Engineering at Karunya Institute of Technology and Science and his Masters in Microelectronics at Manipal Institute of Technology, he began his postdoctoral research at the University of Alabama, Birmingham. There, he worked on NIH-funded projects. He also conducted postdoctoral research at the University of Central Florida. This research included working on DARPA, NSF, and RBC-funded projects. His publications include research articles in highly selective artificial intelligence venues. Dr. Fernandes's current area of research is focused on using artificial intelligence techniques to extract useful patterns from big data. This includes robust computer vision applications using deep learning and computer-aided diagnosis using medical image processing.

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