• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文学位 >A computer aid for the detection of suspicious microcalcification clusters in digitized mammograms.
【24h】

A computer aid for the detection of suspicious microcalcification clusters in digitized mammograms.

机译：一种计算机辅助工具，用于检测数字化乳房X线照片中的可疑微钙化簇。

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This work focused on the development of a computer-aided diagnosis system for the automatic detection of microcalcification clusters in mammograms. The objective of this study was to develop an accurate computer aid and show its potential as a clinical tool towards the early detection of breast cancer.; The design and evaluation of the algorithm involved three main phases. In the first phase of the algorithm, a method was developed for the automated detection of microcalcification clusters. Method development involved extracting histogram features describing individual microcalcifications and cluster features describing microcalcification clusters and designing rule-based classifiers incorporating these features. A database of 98 images was used during this phase for adjusting the parameters and for initial assessment of the method. For the first phase, parameters of the algorithm were adjusted manually since the objective was to examine the discriminating ability of the features towards the accurate detection of microcalcification clusters.; In the second phase of the algorithm, a method for automatic parameter optimization of the CAD scheme was developed. The objectives of the second phase were: (a) to make the training of the algorithm practical, (b) to avoid dependence of the algorithm on subjective rules that might not generalize on a broader population, and (c) to allow the performance evaluation of the algorithm using FROC analysis. The result of the second phase was a neural network-based algorithm.; In the third and last phase of the algorithm, the neural network-based algorithm was retrained and evaluated on an independent, publicly available database to examine the ability of the algorithm to generalize its performance on an unknown population and to enable comparisons with methods from different laboratories.; At the conclusion of this work, the algorithm presented herein represents a complete, automated CAD system. The system was designed to allow relatively straightforward re-optimization for different data sets and was carefully evaluated for its ability to generalize to an independent, large, publicly available data set. The performance of the CAD system supports its application as an accurate computer aid for the detection of microcalcification clusters in mammograms.
机译：这项工作专注于开发用于自动检测乳房X线照片中微钙化簇的计算机辅助诊断系统。这项研究的目的是开发一种精确的计算机辅助工具，并展示其作为早期发现乳腺癌的临床工具的潜力。该算法的设计和评估涉及三个主要阶段。在算法的第一阶段，开发了一种自动检测微钙化簇的方法。方法开发涉及提取描述单个微钙化的直方图特征和描述微钙化聚类的聚类特征，并设计包含这些特征的基于规则的分类器。在此阶段，使用98个图像的数据库来调整参数和对该方法进行初始评估。对于第一阶段，由于目的是检查特征对微钙化簇的准确检测的区分能力，因此手动调整算法的参数。在算法的第二阶段，开发了一种用于CAD方案的自动参数优化的方法。第二阶段的目标是：（a）使算法的培训切实可行，（b）避免算法依赖于可能无法推广到更广泛人群的主观规则，（c）进行性能评估使用FROC分析的算法第二阶段的结果是基于神经网络的算法。在算法的第三阶段和最后阶段，对基于神经网络的算法进行了重新训练，并在一​​个独立的，可公开获得的数据库中进行了评估，以检查该算法将其性能推广到未知种群上的能力，并能够与来自不同人群的方法进行比较实验室。在这项工作结束时，本文介绍的算法代表了一个完整的自动化CAD系统。该系统旨在允许对不同的数据集进行相对直接的重新优化，并经过仔细评估，可以概括为一个独立的，大型的，公开可用的数据集。 CAD系统的性能支持其作为检测乳房X线照片中微钙化簇的精确计算机辅助工具的应用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号