Incorporation of a Laguerre-Gauss channelized Hotelling observer for false-positive reduction in a mammographic mass CAD system.
Previously, we developed a simple Laguerre-Gauss (LG) channelized Hotelling observer (CHO) for incorporation into our mass computer-aided detection (CAD) system. This LG-CHO was trained using initial detection suspicious region data and was empirically optimized for free parameters. For the study presented in this paper, we wish to create a more optimal mass detection observer based on a novel combination of LG channels. A large set of LG channels with differing free parameters was created. Each of these channels was applied to the suspicious regions, and an output test statistic was determined. A stepwise feature selection algorithm was used to determine which LG channels would combine best to detect masses. These channels were combined using a HO to create a single template for the mass CAD system. Results from free-response receiver operating characteristic curves demonstrated that the incorporation of the novel LG-CHO into the CAD system slightly improved performance in high-sensitivity regions.
Baydush
Alan H
AH
Department of Radiation Oncology, Wake Forest University School of Medicine, Medical Center Blvd., Winston-Salem, NC 27157, USA. abaydush@wfubmc.edu
Catarious
David M
DM
Lo
Joseph Y
JY
Floyd
Carey E
CE
D000465:Algorithms; D019540:Area Under Curve; D001185:Artificial Intelligence; D001940:Breast / Q000473:pathology; D001943:Breast Neoplasms / Q000000981:diagnostic imaging; D019992:Databases as Topic; D003661:Decision Support Techniques; D003936:Diagnosis, Computer-Assisted; D005189:False Positive Reactions; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008327:Mammography / Q000706:statistics & numerical data; D010363:Pattern Recognition, Automated; D012372:ROC Curve; D011857:Radiographic Image Interpretation, Computer-Assisted