| Biomedical Image Analysis Contributor(s): Acton, Scott T. (Author) |
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ISBN: 1598290185 ISBN-13: 9781598290189 Publisher: Morgan & Claypool OUR PRICE: $38.00 Product Type: Paperback - Other Formats Published: March 2006 * Not available - Not in print at this time * |
| Additional Information |
| BISAC Categories: - Medical | Diagnostic Imaging - General - Technology & Engineering | Imaging Systems - Technology & Engineering | Biomedical |
| Dewey: 616 |
| Series: Synthesis Lectures on Image, and Multimedia Processing |
| Physical Information: 0.32" H x 7.49" W x 9.24" (0.61 lbs) 144 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: In biological and medical imaging applications, tracking objects in motion is a critical task. This book describes the state-of-the-art in biomedical tracking techniques. We begin by detailing methods for tracking using active contours, which have been highly successful in biomedical applications. The book next covers the major probabilistic methods for tracking. Starting with the basic Bayesian model, we describe the Kalman filter and conventional tracking methods that use centroid and correlation measurements for target detection. Innovations such as the extended Kalman filter and the interacting multiple model open the door to capturing complex biological objects in motion. A salient highlight of the book is the introduction of the recently emerged particle filter, which promises to solve tracking problems that were previously intractable by conventional means. Another unique feature of Biomedical Image Analysis: Tracking is the explanation of shape-based methods for biomedical image analysis. Methods for both rigid and nonrigid objects are depicted. Each chapter in the book puts forth biomedical case studies that illustrate the methods in action. In biological and medical imaging applications, tracking objects in motion is a critical task. This book describes the state-of-the-art in biomedical tracking techniques. We begin by detailing methods for tracking using active contours, which have been highly successful in biomedical applications. The book next covers the major probabilistic methods for tracking. Starting with the basic Bayesian model, we describe the Kalman filter and conventional tracking methods that use centroid and correlation measurements for target detection. Innovations such as the extended Kalman filter and the interacting multiple model open the door to capturing complex biological objects in motion. |