Abstract: A filter assembly comprises a planar first optical filter, a planar second optical filter, a frame-shaped base part for accommodating the first and second optical filters, wherein the base part comprises a support part for supporting edge portions of lower surfaces of the first and second optical filters, and a wall part for laterally enclosing at least part of the first and second optical filters, and one or more clamp parts for securing the first and second optical filters against the base part when the first and second optical filters are inserted into the base part, by contacting upper surfaces of the first and second optical filters and pressing the first and second optical filters towards the support part. The disclosure further relates to a method of manufacturing such filter assembly.

Abstract: In a computer-implemented method for parameterizing an imaging system for mapping a clothed person, image data about the clothed person is obtained and body-shape information about the person is determined by applying a trained machine-learning model to the image data. At least one imaging parameter of the imaging system is determined as a function of the body-shape information.

Abstract: A fundamental machine learning model, fMLM, is provisioned in the untrained or in a partially trained state to provide a trained machine learning model for feature extraction, xMLM, from medical data, wherein the fMLM has an architecture that is trainable by way of unsupervised or self-supervised training. The fMLM has the xMLM and at least one downstream machine learning model, nMLM, for performing at least one corresponding downstream task. First medical data is obtained and the fMLM is trained in an unsupervised or a self-supervised manner based on the first medical data. The xMLM is taken from trained fMLM and stored.

Abstract: A method for AI-assisted generating an adapted medical image processing chain comprises receiving medical image data representing only a piece of information of a complete matching pair of medical image data related to a target flavor, wherein a missing piece of information of the complete matching pair is missing. The method also comprises generating an estimated medical image by applying a medical image processing chain to a raw projection medical image that is related to the received medical image data. Further, the method comprises determining a result of a comparison based on the estimated medical image and a target medical image which is also related to the received medical image data. The method furthermore comprises generating an adapted medical image processing chain by adapting the medical image processing chain based on the result of the comparison. The missing piece of information is generated based on the received medical image data.

Abstract: A filter assembly comprises a planar first optical filter, a planar second optical filter, a frame-shaped base part for accommodating the first and second optical filters, wherein the base part comprises a support part for supporting edge portions of lower surfaces of the first and second optical filters, and a wall part for laterally enclosing at least part of the first and second optical filters, and one or more clamp parts for securing the first and second optical filters against the base part when the first and second optical filters are inserted into the base part, by contacting upper surfaces of the first and second optical filters and pressing the first and second optical filters towards the support part. The disclosure further relates to a method of manufacturing such filter assembly.