Optimized prostate biopsy via a statistical atlas of cancer spatial distribution

被引：66

作者：

Shen, DG

Lao, QQ

Zeng, JC

Zhang, W

Sesterhenn, IA

Sun, L

Moul, JW

Herskovits, EH

Fichtinger, G

Davatzikos, C

机构：

[1] Univ Penn, Dept Radiol, Philadelphia, PA 19104 USA

[2] Johns Hopkins Univ, Ctr Comp Integrated Surg Syst & Technol, Baltimore, MD USA

[3] Howard Univ, Dept Elect & Comp Engn, Washington, DC 20059 USA

[4] Armed Forces Inst Pathol, Washington, DC 20306 USA

[5] DoD Ctr Prostate Dis Res, Rockville, MD 20852 USA

来源：

MEDICAL IMAGE ANALYSIS | 2004年 / 8卷 / 02期

基金：

美国国家科学基金会;

关键词：

prostate cancer; statistical atlas; deformable registration; image warping; image normalization; needle biopsy;

D O I：

10.1016/j.media.2003.11.002

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A methodology is presented for constructing a statistical atlas of spatial distribution of prostate cancer from a large patient cohort, and it is used for optimizing needle biopsy. An adaptive-focus deformable model is used for the spatial normalization and registration of 100 prostate histological samples, which were provided by the Center for Prostate Disease Research of the US Department of Defense, resulting in a statistical atlas of spatial distribution of prostate cancer. Based on this atlas, a statistical predictive model was developed to optimize the needle biopsy sites, by maximizing the probability of detecting cancer. Experimental results using cross-validation show that the proposed method can detect cancer with a 99% success rate using seven needles, in these samples. (C) 2003 Elsevier B.V. All rights reserved.

引用

页码：139 / 150

页数：12

共 22 条

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