Abstract: A method is for determining a patient-adjusted breast compression in mammography. In an embodiment of the method, input data including individual, person-related data of a female patient, is determined. Furthermore, an adjusted individual compression point is determined by applying a function, trained by an algorithm based on machine learning, to the input data. The adjusted individual compression point is generated as the output data. Other embodiments include a method for providing a trained function; a breast compression determining device; a training device; and a mammography system.

Abstract: One or more example embodiments of the present invention relates to a mammography system for recording an X-ray recording dataset of a region of interest of a breast of an examinee, comprising a compression unit for fixing the breast for the recording; and an interrupt unit triggerable by the examinee and connected to the compression unit and an X-ray source, the interrupt unit being configured to release the fixation and to stop the X-ray radiation.

Abstract: One or more example embodiments of the present invention relates to a breast fixation element for a mammography system having a flat elastic surface element including a fastening element for fixing the breast to a support surface of the mammography system, wherein a shape of the breast fixation element is adapted to a shape of the breast.

Abstract: A method is for determining a patient-adjusted breast compression in mammography. In an embodiment of the method, input data including individual, person-related data of a female patient, is determined. Furthermore, an adjusted individual compression point is determined by applying a function, trained by an algorithm based on machine learning, to the input data. The adjusted individual compression point is generated as the output data. Other embodiments include a method for providing a trained function; a breast compression determining device; a training device; and a mammography system.