| Paper: | IMDSP-P9.3 | ||
| Session: | Image and Multidimensional Signal Processing: Applications II | ||
| Time: | Thursday, May 20, 13:00 - 15:00 | ||
| Presentation: | Poster | ||
| Topic: | Image and Multidimensional Signal Processing: Image and Video Analysis | ||
| Title: | SEGMENTATION OF PROSTATE CONTOURS FROM ULTRASOUND IMAGES | ||
| Authors: | Purang Abolmaesumi; Queen's University | ||
| Mohammad Sirouspour; McMaster University | |||
| Abstract: | This paper presents a novel segmentation technique to extractprostate contours from Transrectal Ultrasound (TRUS) images. ASticks Filter is first used to reduce the speckle and enhance the image contrast. The problem is then discretized by projecting equispaced radii from an arbitrary seed point inside the prostate cavity towards its boundary. The distance of the prostate boundary from the seed point is modeled by the trajectory of a moving object. The motion of this moving object is assumed to be governed by a finite set of dynamical models subject to uncertainty. Candidate edge points obtained along each radius include the measurement of the object position and some false returns. This modeling approach enables us to employ the interacting multiple model (IMM) estimator along with a probabilistic data association filter (PDAF) for prostate contour extraction. Since the method does not employ any numerical optimization, convergence is very fast. The stability and accuracy of the method is demonstrated by segmenting contours from a series of prostate ultrasound images. | ||
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