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Proceedings Paper

Model-supported virtual environment for prostate cancer pattern analysis
Author(s): Ping Yu; Maxine A. McClain; Jianhua Xuan; Yue Joseph Wang; Isabell A. Sesterhenn; Judd W. Moul; Wei Zhang; Seong Ki Mun
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Paper Abstract

As a step toward understanding complex spatial distribution patterns of prostate cancers, a 3D master model of the prostate, showing major anatomical structures and probability maps of the location of tumors, has been pilot developed. A virtual environment supported by the 3D master model and in vivo imaging features, will be used to evaluate, simulate, and optimize the image guided needle biopsy and radiation therapy, thus potentially improving the efficacy of prostate cancer diagnosis, staging, and treatment. A deformable graphics algorithm has been developed to reconstruct the graphics models from 200 serially sectioned whole mount radical prostatectomy specimens and to support computerized needle biopsy simulations. For the construction of a generic model, a principal-axes 3D registration technique has been developed. Simulated evaluation and real data experiment have shown the satisfactory performance of the method in constructing initial generic model with localized prostate cancer placement. For the construction of statistical model, a blended model registration technique is advanced to perform a non-linear warping of the individual model to the generic model so that the prostate cancer probability distribution maps can be accurately positioned. The method uses a spine- surface model and a linear elastic model to dynamically deform both the surface and volume where object re-slicing is required. For the interactive visualization of the 3D master model, four modes of data display are developed: (1) transparent rendering of the generic model, (2) overlaid rendering of cancer distributions, (3) stereo rendering, and (4) true volumetric display, and a model-to-image registration technique using synthetic image phantoms is under investigation. Preliminary results have shown that use of this master model allows correct understanding of prostate cancer distribution patterns and rational optimization of prostate biopsy and radiation therapy strategies.

Paper Details

Date Published: 26 May 1999
PDF: 11 pages
Proc. SPIE 3658, Medical Imaging 1999: Image Display, (26 May 1999); doi: 10.1117/12.349418
Show Author Affiliations
Ping Yu, Catholic Univ. of America (United States)
Maxine A. McClain, Catholic Univ. of America (United States)
Jianhua Xuan, Catholic Univ. of America (United States)
Yue Joseph Wang, Catholic Univ. of America (United States)
Isabell A. Sesterhenn, Armed Forces Institute of Pathology (United States)
Judd W. Moul, Uniformed Services Univ. of the Health Sciences (United States)
Wei Zhang, Armed Forces Institute of Pathology (United States)
Seong Ki Mun, Georgetown Univ. Medical Ctr. (United States)


Published in SPIE Proceedings Vol. 3658:
Medical Imaging 1999: Image Display
Seong Ki Mun; Yongmin Kim, Editor(s)

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