人工智能
乳腺摄影术
模式识别(心理学)
特征提取
计算机科学
特征(语言学)
形状分析(程序分析)
集合(抽象数据类型)
度量(数据仓库)
计算机视觉
医学
数据挖掘
乳腺癌
癌症
静态分析
内科学
哲学
语言学
程序设计语言
作者
Liang Shen,Rangaraj M. Rangayyan,J. E. Leo Desautels
出处
期刊:IEEE Transactions on Medical Imaging
[Institute of Electrical and Electronics Engineers]
日期:1994-06-01
卷期号:13 (2): 263-274
被引量:273
摘要
The authors have developed a set of shape factors to measure the roughness of contours of calcifications in mammograms and for use in their classification as malignant or benign. The analysis of mammograms is performed in three stages. First, a region growing technique is used to obtain the contours of calcifications. Then, three measures of shape features, including compactness, moments, and Fourier descriptors are computed for each region. Finally, their applicability for classification is studied by using the three shape measures to form feature vectors. Classification of 143 calcifications from 18 biopsy-proven cases as benign or malignant using the three measures with the nearest-neighbor method was 100% accurate.< >
科研通智能强力驱动
Strongly Powered by AbleSci AI