Abstract: A method for generating protocol data of a specific medical process is described. The specific medical process comprises at least one measurement process preferably a radiological imaging process. The method comprises generating a first structured medical data object based on user-generated electronic medical data. The user-generated electronic medical data are created by an expert documenting the specific medical process. Further, the method includes generating a second structured medical data object by applying an automatic processing algorithm to automatically created electronic medical data. The electronic medical data refer to the specific medical process. Furthermore, the method comprises generating the protocol data based on the first structured medical data object and on the second structured medical data object, wherein the first and second structured medical data objects are compared to determine deviations. Moreover, a protocol data generation device is described.

Abstract: A method for automatically analysing 2D medical image data, including an additional object comprises acquiring the 2D medical image data from an examination portion of a patient using a first modality; acquiring additional image data from the examination portion using a different modality; and performing an automatic image analysis based on the acquired 2D medical image data and the acquired additional image data, the image analysis being adapted to the additional object.

Abstract: A computer-implemented method comprises: obtaining a medical imaging dataset of a current examination of a patient; determining, based on the medical imaging dataset, one or more diagnostic cues using a processing algorithm, wherein the one or more diagnostic cues are associated with patient-specific diagnostic findings; and controlling a user interface to pose the one or more diagnostic cues to a user, as part of a workflow for drawing up a current medical report for the current examination.

Abstract: A framework for personalized recommendation. An image content profile for a current case is generated. One or more auxiliary information representations associated with the current case are further generated. Affinity scores for radiology service providers are then determined by applying service profiles of the radiology service providers, the image content profile and the one or more auxiliary information representations to a trained recommendation engine. The current case is then assigned to one of the radiology service providers based on the affinity scores.

Abstract: A method for evaluation of medical image data comprises: providing medical image data of a patient to be examined; determining, for at least one segment of the medical image data, a respective classification probability value with respect to at least one classification from a list of specified classifications; determining a patient-specific relevance criterion for at least one classification for at least the at least one segment of the medical image data; and determining a clinical relevance of the at least one classification for the at least one segment of the medical image data using the patient-specific relevance criterion, and at least one of based on the classification probability values or based on the at least one segment of the medical image data.

Abstract: Techniques are described to infer 2-D segmentations of a region of interest using a neural network algorithm. Techniques are described to train the neural network algorithm. The 2-D segmentations are determined based on multiple 2-D projection images. For example, x-ray images can be used as an input.

Abstract: A computer-implemented method is for providing at least one first metadata attribute associated with a medical image. The method includes receiving the medical image and the at least one first metadata attribute. Therein the at least one first metadata attribute includes an attribute tag and a provisional attribute value. Furthermore, the method includes applying a first trained function to the medical image to determine an image-based attribute value. Furthermore, the method includes determining a final attribute value based on the provisional attribute value and the image-based attribute value. Furthermore, the method includes providing the at least one first metadata attribute. Therein the at least one first metadata attribute includes the attribute tag and the final attribute value.