Abstract: A clinical decision support system (CDSS) includes a CDSS module comprising a digital processing device configured to store patient data and a clinical guideline. The clinical guideline comprises connected nodes representing clinical workflow events, actions, or decisions, wherein contiguous groups of the nodes are grouped into care phases. The CDSS module is configured to associate patient data with patient care phases selected from the care phases of the clinical guideline, and determine patient care phase time intervals for the patient care phases based on acquisition date information for the patient data associated with the patient care phases. The selected patient care phase may be a care phase associated with a clinical guideline node associated with the new patient data, or may be a patient care phase that is consistent with the acquisition date for the new patient data.

Abstract: A therapy planner is configured to construct a therapy plan based on a planning image segmented into segments delineating features of a subject. A predictive plan adaptation module is configured to adjust the segments to represent a foreseeable change in the subject and to invoke the therapy planner to construct a therapy plan corresponding to the foreseeable change. A data storage stores a plurality of therapy plans generated for a subject by the therapy planner and the predictive plan adaptation module based on at least one planning image of the subject. A therapy plan selector is configured to select one of the plurality of therapy plans for use in a therapy session based on a preparatory image acquired preparatory to the therapy session.

Abstract: A perfusion analysis system includes a perfusion modeller and a user interface. The perfusion modeller generates a patient specific perfusion model based on medical imaging perfusion data for the patient, a general perfusion model, and a quantification of one or more identified pathologies of the patient that affect perfusion in the patient. The user interface accepts an input indicative of a modification to the quantification of the one or more identified pathologies. In response, the perfusion modeller updates the patient specific perfusion model based on the medical imaging perfusion data for the patient, the general perfusion model, and the quantification of the one or more identified pathologies of the patient, including the modification thereto.

Abstract: A therapy planner (16) is configured to construct a therapy plan based on a planning image segmented into segments delineating features of a subject. A predictive plan adaptation module (20) is configured to adjust the segments to represent a foreseeable change in the subject and to invoke the therapy planner to construct a therapy plan corresponding to the foreseeable change. A data storage (18) stores a plurality of therapy plans generated for a subject by the therapy planner and the predictive plan adaptation module based on at least one planning image of the subject. A therapy plan selector (30) is configured to select one of the plurality of therapy plans for use in a therapy session based on a preparatory image acquired preparatory to the therapy session.

Abstract: A perfusion analysis system includes a perfusion modeller and a user interface. The perfusion modeller generates a patient specific perfusion model based on medical imaging perfusion data for the patient, a general perfusion model, and a quantification of one or more identified pathologies of the patient that affect perfusion in the patient. The user interface accepts an input indicative of a modification to the quantification of the one or more identified pathologies. In response, the perfusion modeller updates the patient specific perfusion model based on the medical imaging perfusion data for the patient, the general perfusion model, and the quantification of the one or more identified pathologies of the patient, including the modification thereto.

Abstract: Image registration very often used to be a tedious task which had to be performed manually. According to an exemplary embodiment of the present invention, a non-rigid image registration by an iterative refinement process based on a combination of landmarks with similarity values is proposed. Advantageously, a very fast and robust method maybe provided.

Abstract: A perfusion analysis system includes a perfusion modeller (120) and a user interface (122). The perfusion modeller (120) generates a patient specific perfusion model based on medical imaging perfusion data for the patient, a general perfusion model, and a quantification of one or more identified pathologies of the patient that affect perfusion in the patient. The user interface (122) accepts an input indicative of a modification to the quantification of the one or more identified pathologies. In response, the perfusion modeller (120) updates the patient specific perfusion model based on the medical imaging perfusion data for the patient, the general perfusion model, and the quantification of the one or more identified pathologies of the patient, including the modification thereto.

Abstract: Image registration very often used to be a tedious task which had to be performed manually. According to an exemplary embodiment of the present invention, a registration of image time series is performed on the basis of a pharmacokinetic model in which alternative translation sequences of a region of interest are compared to each other on the basis of the pharmacokinetic model and the best translation vector sequence is used for image registration. Advantageously, this may allow for an effective compensation of organ movement, even if there is no or only little anatomical contrast.

Abstract: Image registration very often used to be a tedious task which had Si to be performed manually. According to an exemplary embodiment of the present invention, a non-rigid image registration by an iterative refinement process based on a combination of landmarks with similarity values is proposed. Advantageously, a very fast and robust method maybe provided.

Abstract: The invention relates to a patient data processing system as well as to a corresponding method for the protocol-driven processing of patient data.

Abstract: A projection display system comprises a presentation computer (1) which generates images which are projected onto a screen (4) using a projector (3) controlled over a line (2) by the computer (1). A video camera (5) views the screen and a laser pointer (8) is supplied for pointing at the screen (4). An interaction computer (7) analyses the signal produced by the video camera (5) to determine the position of peak value in a frame to locate the point at which the laser pointer (5) is pointed. The laser pointer (6) is provided with buttons (10) which perform conventional computer mouse button functions. The state of the buttons (10) may be signalled to the computer (7) over an infra red link (9).

Abstract: The invention relates to an image processing method for improving the signal-to-noise ratio for a series of MR images or CT images which are based on the projection-reconstruction method. First the pixels which reproduce the same sub-structure in the projection images are determined in the one-dimensional projection images constituting the two-dimensional MR or CT images. The image values of these pixels are subjected to noise filtering. Two-dimensional MR images or CT images are reconstructed from the noise filtered one-dimensional projection images.