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Computerized detection of masses in digitized mammograms using single-image segmentation and a multilayer topographic feature analysis.

B Zheng·Y H Chang·D Gur
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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.

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AlgorithmsBreast NeoplasmsDiagnosis, Computer-AssistedFemaleHumansImage EnhancementMammographySensitivity and SpecificityJournal Article

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BibTeXRIS

B Zheng, Y H Chang, D Gur. 1995. Computerized detection of masses in digitized mammograms using single-image segmentation and a multilayer topographic feature analysis.. https://doi.org/10.1016/s1076-6332(05)80696-8

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