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Proceedings Paper

3D MR image segmentation of prostate gland using two scan planes and Fourier descriptor technique
Author(s): Pi Chih Wang; Kang-Ping Lin; Shyhliang A. Lou; Hong-Dun Lin; Te-Shin Chen
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Paper Abstract

The purpose of this paper is to develop a method for prostate gland segmentation in MR image by combining the two scan planes and Fourier descriptor technique. Because not all of the prostate gland in MR image slices have clear boundary that between a prostate gland and its surrounding soft tissues. In this study, the paper improves the problems by using the two scan planes method. And, reconstructing the prostate gland by the image deformable model that integrates the Fourier descriptor method and energy continuity concept. The two scan planes method uses two MR prostate image sets; one is axial and the other is coronal. The coronal image set is for supplementing the base and the apex regions of the prostate gland in the axial image set. By this method, the prostate gland segmentation in MR images will be obtained more correctly. Then the known boundary images of the axial and coronal images can be reconstructed to 3-D image by the Fourier descriptor technique. The technique of this study integrates the spatial coordinate, energy continuity concept and Fourier descriptor to describe the objects for time sequence or spatial related images. Therefore, the model of this work can estimates the interpolation or exterpolational images that from the known images and reconstructs them to three-dimensional object efficiently and accurately.

Paper Details

Date Published: 21 May 1999
PDF: 8 pages
Proc. SPIE 3661, Medical Imaging 1999: Image Processing, (21 May 1999); doi: 10.1117/12.348498
Show Author Affiliations
Pi Chih Wang, Chung-Yuan Univ. (Taiwan)
Kang-Ping Lin, Chung-Yuan Univ. (Taiwan)
Shyhliang A. Lou, Univ. of California/San Francisco (Taiwan)
Hong-Dun Lin, Chung-Yuan Univ. (Taiwan)
Te-Shin Chen, Chung-Yuan Univ. (Taiwan)

Published in SPIE Proceedings Vol. 3661:
Medical Imaging 1999: Image Processing
Kenneth M. Hanson, Editor(s)

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