Dept. of Electr. and Comput. Eng., Tennessee Univ., Knoxville, TN.
IEEE Trans Med Imaging. 1990;9(3):233-41. doi: 10.1109/42.57760.
An automated system for detecting and classifying particular types of tumors in digitized mammograms is described. The analysis of mammograms is performed in two stages. First, the system identifies pixel groupings that may correspond to tumors. Next, detected pixel groupings are subjected to classification. The essence of the first processing stage is multiresolution image processing based on fuzzy pyramid linking. The second stage uses a classification hierarchy to identify benign and malignant tumors. Each level of the hierarchy uses deterministic or Bayes classifiers and a particular measurement. The measurements pertain to shape and intensity characteristics of particular types of tumors. The classification hierarchy is organized in such a way that the simplest measurements are used at the top, with the system stepping through the hierarchy only when it cannot classify the detected pixel groupings with certainty.
描述了一种用于在数字化乳房 X 光片中检测和分类特定类型肿瘤的自动系统。乳房 X 光片的分析分两个阶段进行。首先，系统识别可能对应于肿瘤的像素分组。接下来，对检测到的像素分组进行分类。第一处理阶段的本质是基于模糊金字塔链接的多分辨率图像处理。第二阶段使用分类层次结构来识别良性和恶性肿瘤。层次结构的每个级别都使用确定性或贝叶斯分类器和特定的度量。度量与特定类型肿瘤的形状和强度特征有关。分类层次结构的组织方式是，使用最简单的度量值作为顶层，只有在系统无法确定地对检测到的像素分组进行分类时，系统才会通过层次结构进行分类。
