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用于癌组织数字图像分类的形态学特征提取

Morphological feature extraction for the classification of digital images of cancerous tissues.

作者信息

Thiran J P, Macq B

机构信息

Laboratoire de Télécommunications et Télédétection, Université Catholique de Louvain, Belgium.

出版信息

IEEE Trans Biomed Eng. 1996 Oct;43(10):1011-20. doi: 10.1109/10.536902.

Abstract

This paper presents a new method for automatic recognition of cancerous tissues from an image of a microscopic section. Based on the shape and the size analysis of the observed cells, this method provides the physician with nonsubjective numerical values for four criteria of malignancy. This automatic approach is based on mathematical morphology, and more specifically on the use of Geodesy. This technique is used first to remove the background noise from the image and then to operate a segmentation of the nuclei of the cells and an analysis of their shape, their size, and their texture. From the values of the extracted criteria, an automatic classification of the image (cancerous or not) is finally operated.

摘要

本文提出了一种从显微切片图像中自动识别癌组织的新方法。基于对所观察细胞的形状和大小分析,该方法为医生提供了关于四种恶性标准的非主观数值。这种自动方法基于数学形态学,更具体地说是基于大地测量学的应用。该技术首先用于去除图像中的背景噪声,然后对细胞的细胞核进行分割,并分析其形状、大小和纹理。最后,根据提取标准的值对图像进行自动分类(是否为癌组织)。

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