Automatic Labeling of Special Diagnostic Mammography Views from Images and DICOM Headers.

ABSTRACT: Applying state-of-the-art machine learning techniques to medical images requires a thorough selection and normalization of input data. One of such steps in digital mammography screening for breast cancer is the labeling and removal of special diagnostic views, in which diagnostic tools or magnification are applied to assist in assessment of suspicious initial findings. As a common task in medical informatics is prediction of disease and its stage, these special diagnostic views, which are only enriched among the cohort of diseased cases, will bias machine learning disease predictions. In order to automate this process, here, we develop a machine learning pipeline that utilizes both DICOM headers and images to predict such views in an automatic manner, allowing for their removal and the gen

SUBMITTER: Lituiev DS 

PROVIDER: S-EPMC6456464 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature