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Spatially based application of the minimum cross-entropy thresholding algorithm to segment the pectoral muscle in mammograms

机译:空间基于跨熵阈值算法在乳房X线照片中段术中的跨熵阈值算法

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A threshold-based algorithm is presented for the extraction of the pectoral muscle edge in mediolateral oblique view mammograms. The minimum cross-entropy thresholding algorithm is applied to local areas around the pectoral muscle to determine a series of thresholds as a function of area size. Using a model image it is shown that an inflection point in this function corresponds to a threshold that will separate the pectoral muscle from the rest of the breast. Post processing is performed on mammograms to eliminate false positive points of inflection and a straight line is fitted to the detected pectoral boundary in order to smooth jaggedness caused by the non-uniform intensity of the pectoral muscle edge.
机译:提出了一种基于阈值的算法,用于提取Mediolateral Oblique View乳房图中的胸肌边缘。将最小跨熵阈值算法应用于胸肌周围的局部区域,以确定作为面积大小的函数的一系列阈值。使用模型图像显示该功能中的拐点对应于将与乳房的其余部分分离的阈值。在乳房X线照片上执行后处理以消除伪造的伪阳性点,并且直线装配到检测到的胸边界,以平稳由胸肌边缘的不均匀强度引起的锯齿。

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