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Aly A. Farag received the bachelor degree from Cairo University, Egypt and the PhD degree from Purdue University in Electrical Engineering. He also holds master degrees in bioengineering from the Ohio State and the University of Michigan. He is a University Scholar and Professor of Electrical & Computer Engineering at the University of Louisville. Dr. Farag is the founder and director of the Computer Vision and Image Processing Laboratory (CVIP Lab) which focuses on imaging science, computer vision and biomedical imaging. Dr. Farag main research focus is 3D object reconstruction from multimodality imaging, and applications of statistical and variational methods for object segmentation and registration. He has authored over 250 technical papers in the field of image understanding and holds a number patents. He is regular reviewer to a number of professional organizations in the United States and abroad, and a member of the editorial boards of a number journals and international meetings.
Jasjit S. Suri, PhD is an innovator, scientist, a visionary, and industrialist and an internationally known world leader in Biomedical Engineering and Biological Sciences. Dr. Suri has spent over 20 years in the field of biomedical engineering, devices and its management. He received his Doctorate from the University of Washinton, Seattle and Master's in Executive Business Management from Weatherhead, Case Western Reserve University, Cleveland, Ohio. Dr. Suri was crowned with the President's Gold Medal in 1980 and elected as a Fellow of the American Institute for Medical and Biological Engineering.
Deformable Models: Biomedical and Clinical Applications is the first entry in the two-volume set which provides a wide cross-section of the methods and algorithms of variational and Partial-Differential Equations (PDE) methods in biomedical image analysis. The chapters of Deformable Models: Biomedical and Clinical Applications are written by the well-known researchers in this field, and the presentation style goes beyond an intricate abstraction of the theory into real application of the methods and description of the algorithms that were implemented. As such these chapters will serve the main goal of the editors of these two volumes in bringing down to earth the latest in variational and PDE methods in modeling of soft tissues.
Overall, the chapters in the first volume provide an elegant cross-section of the theory and application of variational and PDE approaches in medical image analysis. This volume introduces, discusses, and provides solutions for problems ranging from structural inversion to models for cardiac segmentation, and other applications in medical image analysis. Graduate students and researchers at various levels of familiarity with these techniques will find the volume very useful for understanding the theory and algorithmic implementations. In addition, the various case studies provided demonstrate the power of these techniques in clinical applications.
Researchers at various levels will find these chapters useful to understand the theory, algorithms, and implementation of many of these approaches.
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