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Identification of the breast boundary in mammograms using active contour models.

机译:使用活动轮廓模型在乳房X线照片中识别乳房边界。

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摘要

A method for the identification of the breast boundary in mammograms is presented. The method can be used in the preprocessing stage of a system for computer-aided diagnosis (CAD) of breast cancer and also in the reduction of image file size in picture archiving and communication system applications. The method started with modification of the contrast of the original image. A binarisation procedure was then applied to the image, and the chain-code algorithm was used to find an approximate breast contour. Finally, the identification of the true breast boundary was performed by using the approximate contour as the input to an active contour model algorithm specially tailored for this purpose. After demarcation of the breast boundary, all artifacts outside the breast region were eliminated. The method was applied to 84 medio-lateral oblique mammograms from the Mini-MIAS database. Evaluation of the detected breast boundary was performed based upon the percentage of false-positive and false-negative pixelsdetermined by a quantitative comparison between the contours identified by a radiologist and those identified by the proposed method. The average false positive and false negative rates were 0.41% and 0.58%, respectively. The two radiologists who evaluated the results considered the segmentation results to be acceptable for CAD purposes.
机译:提出了一种在乳腺X线照片中识别乳房边界的方法。该方法可以用于乳腺癌的计算机辅助诊断(CAD)系统的预处理阶段,并且还可以用于减小图片存档和通信系统应用中的图像文件大小。该方法从修改原始图像的对比度开始。然后将二值化程序应用于图像,并使用链码算法找到近似的乳房轮廓。最后,通过使用近似轮廓作为为此目的专门定制的主动轮廓模型算法的输入来执行对真实乳房边界的识别。在划分乳房边界之后,消除了乳房区域以外的所有伪影。该方法已应用于Mini-MIAS数据库中的84个中外侧斜X线钼靶。根据假阳性和假阴性像素的百分比对检测到的乳房边界进行评估,该百分比由放射科医生识别的轮廓与建议的方法识别的轮廓之间的定量比较确定。假阳性和假阴性的平均比率分别为0.41%和0.58%。两位评估结果的放射科医生认为,分割结果对于CAD而言是可以接受的。

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