B Zheng1, Y H Chang, D Gur. 1. Department of Radiology, University of Pittsburgh, PA 15261-0001, USA.
Abstract
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.
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.
Authors: Pamela G Anderson; Angelo Sassaroli; Jana M Kainerstorfer; Nishanth Krishnamurthy; Sirishma Kalli; Shital S Makim; Roger A Graham; Sergio Fantini Journal: J Biomed Opt Date: 2016-10 Impact factor: 3.170