Region based stellate features for classification of mammographic spiculated lesions in computer-aided detection
Dae Hoe Kim, Jae Young Choi, Yong Man Ro · 2012
In this paper, new region-based stellate features have been developed for correctly differentiating spiculated malignant lesions from normal tissues in mammography. The purpose of using proposed features is to reduce the number of false positive that are produced during the detection of suspicious regions in computeraided detection (CAD). It has been well-known that one particularly important characteristic of spiculated lesions is that they have usually radiating patterns of linear spicules. Based on the aforementioned observation, we propose effective region-based stellate features, designed for well representing the stellate pattern information within a given region-of-interest (ROI). In particular, the proposed features are calculated using statistical information of the stellate patterns within local regions of a given ROI. The effectiveness of our stellate features has been successfully tested on two public mammogram databases (DBs).