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Proceedings Paper

3D prostate shape modeling from sparsely acquired 2D images using deformable models
Author(s): Ismail B. Tutar; Sayan Dev Pathak; Yongmin Kim
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Paper Abstract

Intraoperative quality assessment during prostate brachytherapy could improve the clinical outcome by ensuring the delivery of a prescribed tumoricidal radiation dose to the entire prostate gland. Accurate prostate boundary segmentation is an essential first step towards this. Classical segmentation techniques fail to generate a reliable edge map in ultrasound images. Modeling the 3D prostate shape in a deformable model framework could lead to more reliable prostate segmentation since missing information in some parts of the images due to the indistinct prostatic margins could be reconstructed using information in adjacent slices, and the resulting boundary elements could be integrated into a coherent mathematical description. We first experimented with deformable superquadrics to generate 3D surfaces that match the manually-outlined prostate contours. The superquadrics were found to capture the global shape, but had limited capability of modeling local shape variations. Then, closed and tubular surfaces were generated using Fourier descriptors to fit the prostate data. The modeling errors were compared with the disagreement between manual outlines by three experts. The preliminary results from 12 patient data sets show that the Fourier descriptors are capable of generating tubular surfaces that closely match the manual outlines. The minimum number of parameters required to reconstruct a tubular prostate surface with a tolerable error margin is 52.

Paper Details

Date Published: 5 May 2004
PDF: 9 pages
Proc. SPIE 5367, Medical Imaging 2004: Visualization, Image-Guided Procedures, and Display, (5 May 2004); doi: 10.1117/12.536809
Show Author Affiliations
Ismail B. Tutar, Univ. of Washington (United States)
Sayan Dev Pathak, Univ. of Washington (United States)
Yongmin Kim, Univ. of Washington (United States)

Published in SPIE Proceedings Vol. 5367:
Medical Imaging 2004: Visualization, Image-Guided Procedures, and Display
Robert L. Galloway, Editor(s)

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