Probabilistic framework for reliability analysis of information-theoretic CAD systems in mammography.

Probabilistic framework for reliability analysis of information-theoretic CAD systems in mammography.
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乳腺 X 线摄影中信息理论 CAD 系统可靠性分析的概率框架。

DOI:
10.1109/iembs.2006.260500
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发表时间:
2006
期刊:
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
影响因子:
--
通讯作者:
Tourassi,GeorgiaD
Tourassi,GeorgiaD
中科院分区:
--
文献类型:
--
作者:
Habas,PiotrA;Zurada,JacekM;Elmaghraby,AdelS;Tourassi,GeorgiaD

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本研究的目的是开发和评估乳房 X 线摄影中信息论计算机辅助检测 (IT-CAD) 系统可靠性分析的概率框架。这项研究建立在我们之前针对基于特征的可靠性分析技术的工作基础上,该技术专为使用监督学习方案开发的传统 CAD 系统而定制。本研究提出了一个概率框架,以促进可靠性分析技术在非基于特征的基于知识的 CAD 系统中的应用。该研究基于信息论 CAD 系统,该系统是为筛查乳房 X 光检查数字数据库 (DDSM) 中的肿块检测而开发的。实验结果表明,所提出的概率框架提供的特定于查询的可靠性估计可以准确预测查询情况的 CAD 性能。它还可以成功地应用于将 CAD 预测分层为有临床意义的可靠性组(即高、中和低)。基于留一抽样方案和 ROC 分析,研究表明,对于高可靠性 (Az=0.92plusmn0.03) 的病例,IT-CAD 的诊断性能明显高于那些分层为中 (Az=0.84plusmn0.02) 或低可靠性预测 (Az=0.78plusmn0.02) 的病例。
The purpose of this study is to develop and evaluate a probabilistic framework for reliability analysis of information-theoretic computer-assisted detection (IT-CAD) systems in mammography. The study builds upon our previous work on a feature-based reliability analysis technique tailored to traditional CAD systems developed with a supervised learning scheme. The present study proposes a probabilistic framework to facilitate application of the reliability analysis technique for knowledge-based CAD systems that are not feature-based. The study was based on an information-theoretic CAD system developed for detection of masses in screening mammograms from the Digital Database for Screening Mammography (DDSM). The experimental results reveal that the query-specific reliability estimate provided by the proposed probabilistic framework is an accurate predictor of CAD performance for the query case. It can also be successfully applied as a base for stratification of CAD predictions into clinically meaningful reliability groups (i.e., HIGH, MEDIUM, and LOW). Based on a leave-one-out sampling scheme and ROC analysis, the study demonstrated that the diagnostic performance of the IT-CAD is significantly higher for cases with HIGH reliability (Az=0.92plusmn0.03) than for those stratified as MEDIUM (Az=0.84plusmn0.02) or LOW reliability predictions (Az=0.78plusmn0.02)
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