利用邻域图减少算法对乳腺图像进行病灶分割

Seyyedeh Marziyeh Hamedi, H. E. Komleh
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引用次数: 0

摘要

软组织的分类常常伴随着不确定性,在分割中可能很难测量到最终的区域边界。边缘检测的基本技术可以用来确定医学图像的边界边缘,但由于医学图像中存在噪声和灰度变化较大的问题,很难对图像中病灶的边缘进行合理、精确的分割。本文提出了一种基于图的图像相似区域提取算法,该方法有助于发现相似病灶并进行准确分割。
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Segmentation of breast images to find the lesions using the decreased neighborhood graph algorithm
Classification of soft tissues is often joined with uncertainty and ultimate areas border might be hardly measured in segmentation. Basic techniques of edge detection can be used to determine the boundary edge, but because of noise and gray levels steep changes in medical images, it is difficult to achieve the edge of a lesion in image with reasonable and precise segmentation. In this paper a graph based algorithm is presented to extract alike region in image, this approach helps finding similar lesions and accurate segmentation.
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