Cluster analysis of BI-RADS descriptions of biopsy-proven breast lesions

Mia K. Markey; Joseph Y. Lo; Georgia D. Tourassi; Carey E. Floyd Jr.

doi:10.1117/12.467177

9 May 2002 Cluster analysis of BI-RADS descriptions of biopsy-proven breast lesions

Mia K. Markey, Joseph Y. Lo, Georgia D. Tourassi, Carey E. Floyd Jr.

Proceedings Volume 4684, Medical Imaging 2002: Image Processing; (2002) https://doi.org/10.1117/12.467177
Event: Medical Imaging 2002, 2002, San Diego, California, United States

Abstract

The purpose of this study was to identify and characterize clusters in a heterogeneous breast cancer computer-aided diagnosis database. Identification of subgroups within the database could help elucidate clinical trends and facilitate future model building. Agglomerative hierarchical clustering and k-means clustering were used to identify clusters in a large, heterogeneous computer-aided diagnosis database based on mammographic findings (BI-RADS) and patient age. The clusters were examined in terms of their feature distributions. The clusters showed logical separation of distinct clinical subtypes such as architectural distortions, masses, and calcifications. Moreover, the common subtypes of masses and calcifications were stratified into clusters based on age groupings. The percent of the cases that were malignant was notably different among the clusters. Cluster analysis can provide a powerful tool in discerning the subgroups present in a large, heterogeneous computer-aided diagnosis database.

Citation Download Citation

Mia K. Markey, Joseph Y. Lo, Georgia D. Tourassi, and Carey E. Floyd Jr. "Cluster analysis of BI-RADS descriptions of biopsy-proven breast lesions", Proc. SPIE 4684, Medical Imaging 2002: Image Processing, (9 May 2002); https://doi.org/10.1117/12.467177

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