Using machine learning for quality assurance in mammography
Nowadays, image quality in mammography is determined based on the degree to which fine structures can be detected in a technical phantom. Whereas in the past, the images were examined primarily by radiologists who – successfully (or unsuccessfully) – detected the signals, mathematical procedures (socalled “model observers”) are used today. Several errorprone data processing steps are necessary for this in order to reliably determine the image quality from a number of images.
PTB has developed an alternative procedure using modern machine learning methods. With this procedure, the image quality of mammographs can, for the first time, be determined automatically by means of individual images. The new method is robust and significantly more precise than the procedures used up to now.