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Computers & Graphics
Volume 24, Issue 5, October 2000, Pages 683-694
 
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doi:10.1016/S0097-8493(00)00071-6    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2000 Elsevier Science B.V. All rights reserved.

Dynamic Medical Visualization

Modeling and mapping of prostate cancer

Jianchao ZengCorresponding Author Contact Information, E-mail The Corresponding Author, a, John J. Bauerb and Seong K. Muna

a Imaging Science and Information Systems Center (ISIS), Department of Radiology, Georgetown University Medical Center, 2115 Wisconsin Avenue, NW, Suite 603, Washington, DC 20007, USA b Urology Service, Department of Surgery, Walter Reed Army Medical Center, Washington, DC 20307-5001, USA

Available online 26 October 2000.

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Abstract

Prostate cancer is one of the most common cancers for men. Biopsy of the prostate is carried out following protocols that designate locations and number of needles for tissue sampling as prostate cancer mostly does not show up in the ultrasound images or other modalities. Current protocols for prostate biopsy, however, were created largely based on qualitative clinical experiences and pathological data. They are thus sub-optimal in terms of rate of cancer detection. In fact, the most commonly used protocol (the sextant biopsy) has only about a 30% rate of cancer detection. This leads to more frequent repeat biopsies and potentially runs the risk of not detecting a significant cancer in early stage. In this paper, we aim at improving the performance of prostate needle biopsy by modeling and mapping prostate cancer using real prostate specimens. Surface models of the prostate are reconstructed using deformable modeling techniques. A 3D visualization system is developed to simulate the process of prostate needle biopsy. A 3D distribution map of prostate cancer is built and used to develop optimal biopsy protocols. The 3D map can later be superimposed to online ultrasound images to guide biopsy process of real patients. Experimental results are also provided.

Author Keywords: 3D reconstruction of prostate specimens; Elastic modeling of surface deformation; 3D spatial distribution of prostate cancer; Optimization of prostate needle biopsy

Article Outline

1. Introduction
2. Reconstruction of 3D prostate models
3. Development of a visualization system
4. Spatial distribution of prostate cancer with 281 3D prostate models
4.1. Algorithm for dividing zones and detecting cancers in the zones
4.1.1. 3D-based checking
4.1.2. 2D-based checking
4.2. Two dividing examples
5. Conclusions
Acknowledgements
References





















Computers & Graphics
Volume 24, Issue 5, October 2000, Pages 683-694
 
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