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镉II:用于乳腺X线摄影计算机辅助决策支持的放射学知识获取与呈现

CADMIUM II: acquisition and representation of radiological knowledge for computerized decision support in mammography.

作者信息

Alberdi E, Taylor P, Lee R, Fox J, Sordo M, Todd-Pokropek A

机构信息

CHIME, University College London, UK.

出版信息

Proc AMIA Symp. 2000:7-11.

Abstract

CADMIUM II is a system for the interpretation of mammograms. A novel aspect of the system is that it combines symbolic reasoning with image processing, in contrast with most other approaches, which use only image processing and rely on artificial neural networks (ANNs) to classify mammograms. A problem of ANNs is that the advice they give cannot be traced back to communicable diagnostic inferences. Our approach is to provide advice based on explicit knowledge about the diagnostic process. To this end, we have conducted a knowledge elicitation study which looked at the descriptors used by expert radiologists when making diagnostic decisions about mammograms. The analysis of the radiologists' reports yielded a set of salient diagnostic features. These were used to inform the advice provided by the symbolic decision making component of CADMIUM II.

摘要

镉II是一种用于解读乳房X光片的系统。该系统的一个新颖之处在于,它将符号推理与图像处理相结合,这与大多数其他方法形成对比,其他方法仅使用图像处理并依靠人工神经网络(ANN)对乳房X光片进行分类。人工神经网络的一个问题是,它们给出的建议无法追溯到可传达的诊断推理。我们的方法是基于有关诊断过程的明确知识提供建议。为此,我们进行了一项知识获取研究,该研究着眼于专家放射科医生在对乳房X光片进行诊断决策时使用的描述符。对放射科医生报告的分析产生了一组显著的诊断特征。这些特征被用于为镉II的符号决策组件提供的建议提供信息。

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