Publication | Closed Access
An Evaluation of Contrast Enhancement Techniques for Mammographic Breast Masses
103
Citations
32
References
2005
Year
EngineeringMachine LearningQuantitative MeasuresImage AnalysisData SciencePattern RecognitionBreast ImagingBiostatisticsBreast SurgerySingle Quantitative MeasureRadiologyHealth SciencesMachine VisionMedical ImagingNovel SetContrast AgentDeep LearningImage EnhancementComputer VisionContrast Enhancement TechniquesBreast CancerComputer-aided DiagnosisMedical Image AnalysisImage Segmentation
The main aim of this paper is to propose a novel set of metrics that measure the quality of the image enhancement of mammographic images in a computer-aided detection framework aimed at automatically finding masses using machine learning techniques. Our methodology includes a novel mechanism for the combination of the metrics proposed into a single quantitative measure. We have evaluated our methodology on 200 images from the publicly available digital database for screening mammograms. We show that the quantitative measures help us select the best suited image enhancement on a per mammogram basis, which improves the quality of subsequent image segmentation much better than using the same enhancement method for all mammograms.
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