首页> 外文会议>Conference on Medical Image Acquisition and Processing Oct 23-24, 2001, Wuhan, China >A Region-Growing Approach to Detect Microcalcifications in Digital Mammograms
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A Region-Growing Approach to Detect Microcalcifications in Digital Mammograms

机译:检测数字化乳腺X线照片中微钙化的区域生长方法

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Detecting early symptoms of breast cancer is very important to enhance the possibility of cure. There have been active researches to develop computer-aided diagnosis(CAD) systems detecting early symptoms of breast cancer in digital mammograms. An expert or a CAD system can recognize the early symptoms based on microcalcifications appeared in digital mammographic images. Microcalcifications have higher gray value than surrounding regions, so these can be detected by expanding a region from a local maximum. However the resultant image contains unnecessary elements such as noise, holes and valleys. Mathematical morphology is a good solution to delete regions that are affected by the unnecessary elements. In this paper, we present a method that effectively detects microcalcifications in digital mammograms using a combination of local maximum operation and the region-growing operation.
机译:检测乳腺癌的早期症状对于提高治愈的可能性非常重要。已经开展了积极的研究来开发计算机辅助诊断(CAD)系统,以在数字乳房X线照片中检测乳腺癌的早期症状。专家或CAD系统可以根据乳腺X线照片中出现的微钙化来识别早期症状。微钙化具有比周围区域更高的灰度值,因此可以通过从局部最大值扩展区域来检测它们。但是,生成的图像包含不必要的元素,例如噪音,空洞和凹谷。数学形态学是删除受不必要元素影响的区域的好方法。在本文中,我们提出了一种结合局部最大操作和区域增长操作有效检测数字乳房X线照片中的微钙化的方法。

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