Abstract:
Methods related to survey scanning in diagnostic medical imaging. At least one aspect relates to a method for generating, using a machine learning model, a simulation of medical image data in accordance with a defined set of acquisition parameters for a medical imaging apparatus, based on processing of an initial 3D image data set (e.g. a survey image dataset).
Abstract:
An X-ray imaging system (100) includes an X-ray source (110), an X-ray detector (120), a depth camera (130), and a processor (140). The processor (140) receives depth camera image data from the depth camera, projects the depth camera image data onto a radiation-receiving surface of the X-ray detector (120), from a perspective of the X-ray source (110), and generates an image representation (170) of the projected depth camera image data on the radiation-receiving surface of the X-ray detector (120), from a perspective of the depth camera (130).
Abstract:
The invention provides for a magnetic resonance imaging system (100) for acquiring magnetic resonance data (154) from an imaging zone (108). The magnetic resonance imaging system comprises: a memory (136) for storing initial pulse sequence commands (140) and machine executable instructions (160); and a processor (130) for controlling the magnetic resonance imaging system. Execution of the machine executable instructions causes the processor to receive (200) a set of selected pulse sequence parameters (142) comprising a definition of a region of interest (109) of a subject (118). The region of interest is within the imaging zone. Execution of the machine executable instructions further causes the processor to send (202) an image data request to a historical database (138). The image data request comprises the set of selected pulse sequence parameters. Execution of the machine executable instructions further causes the processor to receive (204) historical image data (146, 306, 308, 310, 312, 314, 402) from the historical database in response to the image data request. The historical database comprises multiple image data entries. Each image data entry comprises a set of historical pulse sequence parameters (502). The historical database is configured to search the historical database to retrieve the historical image data by matching the set of selected pulse sequence parameters to the set of historical pulse sequence parameters. Execution of the machine executable instructions further causes the processor to display (206) at least a portion (148) of the historical image data on a user interface. Execution of the machine executable instructions further causes the processor to receive (208) scan input modifications (150) in response to displaying the at least a portion of the historical image data on the user interface. Execution of the machine executable instructions further causes the processor to generate (210) modified pulse sequence commands (152) using the initial pulse sequence commands, the set of selected pulse sequence parameters, and the scan input modifications. Execution of the machine executable instructions further causes the processor to control (212) the magnetic resonance imaging system to acquire the magnetic resonance data using the modified pulse sequence commands.
Abstract:
A system (100) for reconstruction of medical images over a network comprises a scheduler (302) that schedules a reconstruction request (108) and the reconstruction request includes a medical image reconstruction of a subject according to an imaging protocol The scheduling includes scheduling of a plurality of events, each event with a corresponding time, and the plurality of events include at least one event with the corresponding time selected from a group consisting of a first time (520) to transmit raw image data (114) over a first network from a source node (116) to a reconstruction node (106), a second time (522) to reconstruct the medical image (118) by the reconstruction node, and a third time (524) to transmit the reconstructed medical image over a second network from the reconstruction node to a destination node (120).
Abstract:
The present disclosure relates to a method for configuring a medical device. The method comprises: providing a set of one or more parameters for configuring the medical device. Each parameter of the set has predefined values. A set of values of the set of parameters may be selected from the predefined values. Using the selected values the set of parameters may be set, which results in an operational configuration of the medical device. The medical device may be controlled to operate in accordance with the operational configuration, thereby an operating status of the medical device may be determined. Based on at least the operating status the operational configuration may be maintained or the selecting, setting and controlling may be repeatedly performed until a desired operating status of the medical device can be determined based on the operating statuses resulting from the controlling.
Abstract:
A method and related system for supporting task scheduling. Completion times of tasks of a process are predicted based on historical data held in a database (HIS). Based on the predictions, a workload measure for a resource associated with performing the task is computed. Also, there is established whether the predicted completion times will result in overshooting predefined due-dates as held in a rules database (DB-REG). The work load measure and/or the overshoot is indicted as graphical indicators in a graphical user interface (GUI). The workload measure and/or the overshoot indicators are computed and displayed in real-time.