| 摘要 |
A significant metric in federal mammography quality standards is the phantom image quality assessment. A Mammography Quality Control System (MQCS) (20, 20') performs automated image analyses for the American College of Radiology (ACR) mammographic accreditation phantom (MAP) images. The MQCS (20, 20') uses a Fast Fourier Transform unit (41) for low-level processing combined with derivative filters for intermediate-level processing to provide translation and rotation independent localization of test objects in the MAP images. The MQCS (20, 20') uses a Bayesian classifier (47) using threshold contrast. The fifty percent visibility contrast thresholds established by the trained observer's responses were: fibrils 1.010; microcalcifications 1.156; and nodules 1.016. Using these values and given automated localization of test objects, the MQCS (20, 20') scores images with better consistency than the diagnostic physicists. The MQCS (20, 20') thus provides an operator independent, machine-based scoring of MAP images that is used to help eliminate the effect of observer variability. |
