PDE and Level Sets: Algorithmic Approaches to Static and Motion Imagery

PDE & Level Sets: Algorithmic Approaches to Static & Motion Imagery is specially dedicated to the segmentation of complex shapes from the field of imaging sciences using level sets and PDEs. It covers the fundamentals of level sets, different kinds of concepts of both geodesic curvature flows and planar flows, as well as the power of incorporation of regional-statistics in level set framework. In covering this material, this book presents segmentation of object-in-motion imagery based on level sets in eigen analysis framework, while also presenting classical problems of boundary completion in cognitive images, like the pop-up of subjective contours in the famous triangle of Kanizsa using surface evolution framework, or the mean curvature evolution of a graph with respect to the Riemannian metric induced by the image. All results are presented for modal completion of cognitive objects with missing boundaries.

Book Series: Topics In Biomedical Engineering

In the medical field, medical imagery has come to be a discipline of its own, given the nature of its applications in the understanding of the human body and medical diagnostics. Image processing techniques are the core tools for solving these biomedical problems. The applications of Level sets has made a significant impact on medical imagery primarily because of its ability to perform efficient topology preservation and fast shape recovery. This has dominated the binary, grayscale and color frameworks, which the eye can perceive. It has not only the ability to find boundaries and surfaces that are deep seated in 2-D and 3-D volumes respectively, but also provide satisfactory solutions for the completion of cognitive objects with missing boundaries.

Presents partial differential equation (PDE) and level set techniques for image sequence segmentation of both still images and moving objects. The eight contributions develop an algorithm for color image segmentation, a geometric model for segmentation of images with missing boundaries, and a fast region-based level set approach for extraction of white matter, gray matter, and cerebrospinal fluid boundaries from MR slices of the brain. The opening chapters review analytical and numerical methods for solving PDEs, illustrate the flexibility of the level set method in different applications, and discuss the role of regularizers in PDEs and the level set framework. Annotation (c)2003 Book News, Inc., Portland, OR

Jasjit Suri, Ph.D. has spent the last 20 years in the field of computer and electrical engineering, and more than a decade in imaging sciences. Dr. Suri has a masters in computer sciences from the University of Illinois, a doctorate from the University of Washington, Seattle, and will soon receive his EMBA from the Weatherhead School of Management at Case Western Reserve University, Cleveland, Ohio. Dr. Suri has published over 100 technical publications in medical imaging, is a senior member of IEEE, member of the engineering honor societies Eta-Kappa-Nu and Tau-Beta-Phi, and a recipient of the President's Gold Medal in 1980.

Prof. Swamy Laxminarayan, D.Sci. championed the field of Biomedical Engineering for over 30 years having held a variety of senior positions within the industry. He is an internationally recognized scientist, engineer, and educator with over 200 technical publications in biomedical information technology, computation biology, signal and image processing, biotechnology, and physiological system modeling. Prof. Laxminarayan is a fellow of AIMBE and a recipient of IEEE 3rd Millennium Medal.