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A Filter-Based Approach Towards Automatic Detection of Microcalcification

机译:基于过滤器的微钙化自动检测方法

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摘要

To establish a practical CAD (Computer-Aided Diagnosis) system to facilitate the diagnosis of microcalcifications, we propose a filter-based technique to detect microcalcifications. Via examination of an existing optimal filter-based technique, it is found that its performance on highlighting the energy of mammograms is seriously affected by artefacts and the background of breast. As a result, four methods in pre and post-processing are described in this paper to improve the optimal filtering, leading to an adaptive selection of thresholds for input mammograms. These methods have been tested by using 30 mammograms (with 25 microcalcifications) from the MIAS database and 23 mammograms from DDSM database. Comparing with the original optimal filter-based technique, our technique reduces the false detections (FD), eliminates the influence of the background in mammograms and is able to adaptively select the threshold for the detection of microcalcifications.
机译:为了建立实用的CAD(计算机辅助诊断)系统以促进微钙化的诊断,我们提出了一种基于过滤器的技术来检测微钙化。通过检查现有的基于过滤器的最佳技术,发现其在突出显示乳房X光照片能量方面的性能受到伪影和乳房背景的严重影响。结果,本文描述了四种预处理和后处理方法,以改善最佳过滤效果,从而为输入乳房X线照片自适应选择阈值。这些方法已通过使用MIAS数据库的30幅乳房X线照片(具有25个微钙化)和DDSM数据库的23幅乳房X线照片进行了测试。与最初的基于最佳过滤器的技术相比,我们的技术减少了错误检测(FD),消除了乳腺X线照片中背景的影响,并且能够自适应地选择检测微钙化的阈值。

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