29 April 2005 Classification of mammographic lesions into BI-RADS shape categories using the beamlet transform
Author Affiliations +
Abstract
We present a new algorithm and preliminary results for classifying lesions into BI-RADS shape categories: round, oval, lobulated, or irregular. By classifying masses into one of these categories, computer aided detection (CAD) systems will be able to provide additional information to radiologists. Thus, such a tool could potentially be used in conjunction with a CAD system to enable greater interaction and personalization. For this classification task, we have developed a new set of features using the Beamlet transform, which is a recently developed multi-scale image analysis transform. We trained a k-Nearest Neighbor classifier using images from the Digital Database for Digital Mammography (DDSM). The method was tested on a set of 25 images of each type and we obtained a classification accuracy of 78% for classifying masses as oval or round and an accuracy of 72% for classifying masses as lobulated or round.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mehul P. Sampat, Mehul P. Sampat, Alan Conrad Bovik, Alan Conrad Bovik, Mia K. Markey, Mia K. Markey, } "Classification of mammographic lesions into BI-RADS shape categories using the beamlet transform", Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); doi: 10.1117/12.596563; https://doi.org/10.1117/12.596563
PROCEEDINGS
10 PAGES


SHARE
Back to Top