Statistically optimized biopsy strategy for the diagnosis of prostate cancer

Dinggang Shen, Z. Lao, J. Zeng, E. H. Herskovits, G. Fichtinger, C. Davatzikos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

This paper presents a method for optimizing prostate needle biopsy, by creating a statistical atlas of the spatial distribution of prostate cancer from a large patient cohort. In order to remove inter-individual morphological variability and to determine the true variability in the spatial distribution of cancer within the prostate, an adaptive-focus deformable model (AFDM) is first used to register and normalize the prostate samples. A probabilistic method is then developed to select the prostate-biopsy strategy that the greatest chance of detecting prostate cancer. For a test set of data from 20 prostate subjects, five needle locations are adequate to detect the tumor 100% of the time. Furthermore, the results on the accuracy of deformable registration and the predictive power of our statistically optimized biopsy strategy are presented in this paper.

Original languageEnglish
Title of host publicationProceedings of the IEEE Symposium on Computer-Based Medical Systems
Pages433-438
Number of pages6
Publication statusPublished - 2001
Externally publishedYes
Event14th IEEE Symposium on Computer-Based Medical Systems - Bethesda, MD, United States
Duration: 2001 Jul 262001 Jul 27

Other

Other14th IEEE Symposium on Computer-Based Medical Systems
CountryUnited States
CityBethesda, MD
Period01/7/2601/7/27

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ASJC Scopus subject areas

  • Software

Cite this

Shen, D., Lao, Z., Zeng, J., Herskovits, E. H., Fichtinger, G., & Davatzikos, C. (2001). Statistically optimized biopsy strategy for the diagnosis of prostate cancer. In Proceedings of the IEEE Symposium on Computer-Based Medical Systems (pp. 433-438)