Biomedical Image Segmentation by Ayman El-Baz - ISBN: 9780367870867
Paperback
As one of the most important tasks in biomedical imaging, image segmentation provides the foundation for quantitative reasoning and diagnostic techniques. A large variety of different imaging techniques, each with its own physical principle and characteristics (e.g., noise modeling), often requires …

Biomedical Image Segmentation

Advances and Trends

$235.86

  • Paperback

    548 pages

  • Release Date

    10 December 2019

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Summary

As one of the most important tasks in biomedical imaging, image segmentation provides the foundation for quantitative reasoning and diagnostic techniques. A large variety of different imaging techniques, each with its own physical principle and characteristics (e.g., noise modeling), often requires modality-specific algorithmic treatment. In recent years, substantial progress has been made to biomedical image segmentation. Biomedical image segmentation is characterized by several specific …

Book Details

ISBN-13:9780367870867
ISBN-10:036787086X
Author:Ayman El-Baz, Xiaoyi Jiang, Jasjit S. Suri
Publisher:Taylor & Francis Ltd
Imprint:CRC Press
Format:Paperback
Number of Pages:548
Release Date:10 December 2019
Weight:453g
Dimensions:254mm x 178mm
What They're Saying

Critics Review

“The book provides a current and thorough overview of some commonly used image segmentation algorithms for medical imaging. The overview of a wide selection of methods is helpful, and I also found it very convenient to see implementation details collected in one single volume. This makes the book a good reference book for both researchers in the field, and could also be helpful for software engineers in the medical industry implementing methods for medical practitioners.”
Kristian Sandberg, Computational Solutions, Inc., Colorado, USA

About The Author

Ayman El-Baz

Ayman El-Baz, Ph.D, is an associate professor in the Department of Bioengineering at the University of Louisville, Kentucky, USA. Dr. El-Baz has twelve years of hands-on experience in the fields of bioimaging modeling and computer-assisted diagnostic systems. He has developed new techniques for analyzing 3D medical images. His work has been reported at several prestigious international conferences (e.g., CVPR, ICCV, MICCAI, etc.) and in journals (e.g., IEEE TIP, IEEE TBME, IEEE TITB, Brain, etc.). His work related to novel image analysis techniques for lung cancer and autism diagnosis have earned him multiple awards, including: first place at the annual Research Louisville 2002, 2005, 2006, 2007, 2008, 2010, 2011 and 2012 meetings, and the “Best Paper Award in Medical Image Processing” from the prestigious ICGST International Conference on Graphics, Vision, and Image Processing (GVIP-2005). Dr. El-Baz has authored or coauthored more than 300 technical articles.

Xiaoyi Jiang studied computer science at Peking University and received his Ph.D and Venia Docendi (Habilitation) degree in computer science from University of Bern, Switzerland. He was an associate professor at Technical University of Berlin, Germany. Since 2002, he has been a full professor of computer science at University of Münster, Germany. Currently, he is editor-in-chief of the Int. Journal of Pattern Recognition and Artificial Intelligence and also serves on the advisory board and editorial board of several journals including Pattern Recognition, IEEE Trans. on Systems, Man, and Cybernetics – Part B, and Chinese Science Bulletin. His research interests include biomedical image analysis, 3D image analysis, and structural pattern recognition. He is a PI of the new Cluster of Excellence “Cells in Motion” funded by the German Excellence Initiative, a senior member of IEEE, and a fellow of IAPR.

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