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Automatic microcalcifications segmentation procedure based on Otsu's method and morphological filters

机译：基于OTSU方法和形态过滤器的自动微钙化分割过程

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Microcalcifications are present in a great number of malignant lesions, being considered as a significant sign of malignancy. However, they are detected in less than 50% of mammograms with carcinomas. Given this scenario, systems to highlight infra-clinic lesions, aiding the specialists to make diagnostics, have been studied. These Computer-aided diagnosis systems have been developed based on parameters extracted from microcalcifications. They are basically composed of three parts: segmentation, parameters calculation and lesions classification. This paper presents an automatic microcalcification segmentation method, based on Otsu's method and morphological filters. The proposed method was assessed with 236 regions of interest, captured from 54 images (300 dpi, 8 bits). Based on the joint opinion of two experienced radiologists, the algorithm adequately segmented at least 88.6% of the cases.
机译：微钙质存在于大量恶性病变中，被认为是恶性肿瘤的重要迹象。 然而，它们在含有癌XMXCOMAS的不到50％的乳腺照片中检测到它们。 鉴于这种情况，已经研究了突出infra诊所病变的系统，辅助专家制作诊断。 这些计算机辅助诊断系统已经基于从微钙化中提取的参数开发。 它们基本上由三个部分组成：分段，参数计算和病变分类。 本文介绍了一种自动微碳化分割方法，基于OTSU的方法和形态过滤器。 通过236个感兴趣区域评估所提出的方法，从54个图像（300 dpi，8位）捕获。 基于两位经验丰富的放射科医师的联合意见，该算法足够分割至少88.6％的病例。

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