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一种评估数字乳腺摄影中病变可检测性的定量方法。

A quantitative method for evaluating the detectability of lesions in digital mammography.

作者信息

Zanca F, Van Ongeval C, Jacobs J, Marchal G, Bosmans H

机构信息

University Hospitals Leuven, Herestraat 49, 3000 Leuven, Belgium.

出版信息

Radiat Prot Dosimetry. 2008;129(1-3):214-8. doi: 10.1093/rpd/ncn049. Epub 2008 Mar 4.

Abstract

This study presents a quantitative method for evaluating the detectability of microcalcifications in digital mammography. Four hundred and twenty microcalcifications (with various morphology, size and contrast), simulated with a previously validated method, were used for the creation of image datasets. Lesions were inserted into 163 regions of interests of 59 selected raw digital mammograms with various anatomical backgrounds and acquired with a Siemens Novation DR. After processing, these composite images were scored by experienced radiologists, who located multiple simulated lesions and rated them under conditions of free-search. For statistical analysis, free-response receiver-operating characteristic curves are plotted; the use of jackknife free-response receiver-operating characteristic method has also been investigated. The main advantage of this methodology is that the exact number of inserted microcalcifications is well known and that the lesions are fully characterised in terms of pathology, size, morphology and peak contrast. A first application has been the evaluation of the effect of anatomical background on microcalcifications detection. Preliminary findings in this study indicate that this method may be a promising tool to evaluate factors that have an influence on the detectability of lesions, such as the clinical processing or the viewing conditions.

摘要

本研究提出了一种用于评估数字乳腺摄影中微钙化灶可检测性的定量方法。使用先前验证过的方法模拟了420个微钙化灶(具有各种形态、大小和对比度),用于创建图像数据集。将病变插入到59幅选定的具有不同解剖背景的原始数字乳腺造影片的163个感兴趣区域中,并使用西门子Novation DR进行采集。处理后,由经验丰富的放射科医生对这些合成图像进行评分,他们在自由搜索条件下定位多个模拟病变并对其进行评级。为了进行统计分析,绘制了自由反应接收者操作特征曲线;还研究了留一法自由反应接收者操作特征方法的使用。该方法的主要优点是,插入的微钙化灶的确切数量是已知的,并且病变在病理学、大小、形态和峰值对比度方面得到了充分表征。第一个应用是评估解剖背景对微钙化灶检测的影响。本研究的初步结果表明,该方法可能是评估影响病变可检测性的因素(如临床处理或观察条件)的一个有前景的工具。

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