期刊名称：Journal of Computing and Information Technology
印刷版ISSN：1330-1136
电子版ISSN：1846-3908
出版年度：1998
卷号：6
期号：4
页码：425-433
语种：English
出版社：SRCE - Sveučilišni računski centar
摘要：Computer-aided diagnosis (CAD) schemes for the detection of microcalcification clusters (MCCs) come in two types: indirect and direct. Indirect detection of MCCs detect individual microcalcifications first, which are then used to detect clusters. Direct detection detects clusters in a unique step, without any previous detection of individual microcalcifications. Nearly all the existing literature describes indirect detection. In this study, we investigated a direct detection scheme. We divided digital mammograms into regions of interest (ROis) and computed a set of parameters on each ROI. We discriminated parameters through an artificial neural network (ANN) that gave the presence or absence of an MCC in the examined ROI. Final images with suspicious ROis containing MCCs were shown to radiologists. Results appeared to be interesting enough to compete with indirect detections. Extra studies could prove direct detection to be a better approach as compared to indirect detection CAD schemes.
关键词：breast cancer; digital mammography; mammograms; artificial neural networks; direct detection; indirect detection; clusters of...
