Computerized detection of masses from digitized mammograms: comparison of single-image segmentation and bilateral-image subtraction.

RATIONALE AND OBJECTIVES Two methods--single-image segmentation and bilateral-image subtraction--have been used commonly as the first stage in computer-aided detection (CAD) schemes to detect masses on digitized mammograms. In the current study, we investigated and compared the advantages and disadvantages of the two methods in achieving a high sensitivity for mass detection. METHODS Two CAD schemes were tested. One used Gaussian filtering based on single-image segmentation, and the other used bilateral-image subtraction based on left-right image pairs to identify suspicious mass regions. A clinical database that contained 152 verified mass cases was used to compare the two approaches. RESULTS The single-image segmentation method yielded 100% sensitivity and had a somewhat higher number of initial suspicious regions. The bilateral-image subtraction method missed several true-positive regions at the initial phase. Each approach achieved more than 90% sensitivity at a false-positive rate of approximately 0.8 per image. CONCLUSION Optimal initial image segmentation schemes may depend on the complete detection and classification method used. Single-image segmentation methods may perform comparably with bilateral-image segmentation schemes, and these techniques appear to be more versatile and easily adaptable to future clinical CAD applications.