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首页> 外文期刊>Procedia Computer Science >Intensity Based Automatic Boundary Identification of Pectoral Muscle in Mammograms
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Intensity Based Automatic Boundary Identification of Pectoral Muscle in Mammograms

机译:基于强度的乳房X光检查中胸肌的自动边界识别

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摘要

The pectoral muscle detection is an important assignment to improve the diagnostic performance of the breast cancer detection. In this paper, we have proposed an intensity based approach for pectoral muscle boundary detection in mammograms. The enhancement filter mask of 3×2, have been proposed and applied on the image to enhance the pectoral region of the mammograms. The pectoral boundary points from the candidates were detected based on threshold technique. Finally, all the boundary points detected were connected to obtain the boundary of pectoral muscle. The proposed technique has been tested on 320 digitized mammograms form mini-Mammographic Image Analysis Society (MIAS) database of 322 mammograms, with an acceptance rate of 96.56% from expert radiologists. The mean False Positive (FP) and False Negative (FN) rate demonstrate the effectiveness of the proposed method.
机译:胸肌检测是提高乳腺癌检测诊断性能的重要任务。在本文中,我们提出了一种基于强度的乳房X光检查中胸肌边界检测方法。已经提出了3×2的增强滤光器掩模并将其应用于图像上以增强乳房X线照片的胸部区域。基于阈值技术检测候选人的胸骨边界点。最后,将所有检测到的边界点连接起来以获得胸肌的边界。所提出的技术已经在322个X线摄影的微型X线摄影图像分析协会(MIAS)数据库中的320个数字化X线摄影照上进行了测试,放射专家的接受率为96.56%。平均误报率(FP)和误报率(FN)证明了该方法的有效性。

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