Abstract
Published research results are difficult to replicate due to the lack of a standard evaluation data set in the area of decision support systems in mammography; most computer-aided diagnosis (CADx) and detection (CADe) algorithms for breast cancer in mammography are evaluated on private data sets or on unspecified subsets of public databases. This causes an inability to directly compare the performance of methods or to replicate prior results. We seek to resolve this substantial challenge by releasing an updated and standardized version of the Digital Database for Screening Mammography (DDSM) for evaluation of future CADx and CADe systems (sometimes referred to generally as CAD) research in mammography. Our data set, the CBIS-DDSM (Curated Breast Imaging Subset of DDSM), includes decompressed images, data selection and curation by trained mammographers, updated mass segmentation and bounding boxes, and pathologic diagnosis for training data, formatted similarly to modern computer vision data sets. The data set contains 753 calcification cases and 891 mass cases, providing a data-set size capable of analyzing decision support systems in mammography.
Highlights
Background & SummaryComputer-aided detection (CADe) and diagnosis (CADx) systems are designed to assist radiologists for mammography interpretation
Current CADe systems are limited by high false-positive rates[1], and CADx systems for mammography are not yet approved for clinical use[2]
The Digital Database for Screening Mammography (DDSM) was developed through a grant from the DOD Breast Cancer Research Program, US Army Research and Material Command, and the necessary patient consents were obtained by the original developers of the DDSM6
Summary
Computer-aided detection (CADe) and diagnosis (CADx) systems are designed to assist radiologists for mammography interpretation. The scale of the database along with ground truth validation makes the DDSM a useful tool in the development and testing of decision support systems despite the fact that the images are scanned film instead of full field digital mammograms. This is because there is currently no mammography database of this size publicly available. We report here the development of, and propose to release, the CBIS-DDSM (Curated Breast Imaging Subset of DDSM), an updated version of the DDSM providing accessible data and improved ROI segmentation This resource will contribute to the advancement of decision support system research in mammography, supplying a standardized mammography data.
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