B Zheng1, Y H Chang, D Gur. 1. Department of Radiology, University of Pittsburgh, PA 15261-0001, USA.
Abstract
RATIONALE AND OBJECTIVES: We developed and evaluated a computer-aided detection (CAD) scheme for masses in digitized mammograms. METHODS: A multistep CAD scheme was developed and tested. The method uses a technique of single-image segmentation with Gaussian bandpass filtering to yield a high sensitivity for mass detection. A rule-based multilayer topographic feature analysis method is then used to classify suspected regions. A set of 260 cases, including 162 verified masses, was divided into two subsets; one set was used to set the rule-based classification and one was used to test the performance of the scheme. RESULTS: In a preliminary clinical study, the implemented detection scheme yielded 98% sensitivity with a false-positive detection rate of less than one false-positive region per image. CONCLUSION: Single-image segmentation methods seem to have high sensitivity in selecting true-positive mass regions in the first stage of a CAD scheme. A multilayer topographic image feature analysis method in the second stage of a CAD scheme has the potential to significantly reduce the false-positive detection rate.
RATIONALE AND OBJECTIVES: We developed and evaluated a computer-aided detection (CAD) scheme for masses in digitized mammograms. METHODS: A multistep CAD scheme was developed and tested. The method uses a technique of single-image segmentation with Gaussian bandpass filtering to yield a high sensitivity for mass detection. A rule-based multilayer topographic feature analysis method is then used to classify suspected regions. A set of 260 cases, including 162 verified masses, was divided into two subsets; one set was used to set the rule-based classification and one was used to test the performance of the scheme. RESULTS: In a preliminary clinical study, the implemented detection scheme yielded 98% sensitivity with a false-positive detection rate of less than one false-positive region per image. CONCLUSION: Single-image segmentation methods seem to have high sensitivity in selecting true-positive mass regions in the first stage of a CAD scheme. A multilayer topographic image feature analysis method in the second stage of a CAD scheme has the potential to significantly reduce the false-positive detection rate.
Authors: Jun Wei; Berkman Sahiner; Lubomir M Hadjiiski; Heang-Ping Chan; Nicholas Petrick; Mark A Helvie; Marilyn A Roubidoux; Jun Ge; Chuan Zhou Journal: Med Phys Date: 2005-09 Impact factor: 4.071
Authors: Jun Wei; Heang-Ping Chan; Berkman Sahiner; Lubomir M Hadjiiski; Mark A Helvie; Marilyn A Roubidoux; Chuan Zhou; Jun Ge Journal: Med Phys Date: 2006-11 Impact factor: 4.071
Authors: Bin Zheng; Claudia Mello-Thoms; Xiao-Hui Wang; Gordon S Abrams; Jules H Sumkin; Denise M Chough; Marie A Ganott; Amy Lu; David Gur Journal: Acad Radiol Date: 2007-08 Impact factor: 3.173