Abstract:
A system, method and non-transitory computer-readable storage medium for monitoring motion during medical imaging. The monitoring of the motion includes initiating an acquisition of image data, measuring physiological signals of a patient, generating a prediction signal by integrating the physiological signals, determining whether patient motion is likely to occur based on the prediction signal and modifying the acquisition of image data, if it is predicted that patient motion is likely to occur.
Abstract:
The exemplary embodiments are related to systems and methods for automatically selecting one or more suitable medical imaging protocols based on a patient's clinical information. Exemplary embodiments relate to methods and systems for collecting clinical information for a current patient, generating an encoded description of a plurality of imaging protocols in a computer-processable format including medical concepts, converting the collected clinical information into the computer-processable format, and recommending or providing at least one suitable imaging protocol based on the encoded description and the converted clinical information for the current patient.
Abstract:
Medical selection system 100 for generating selection data, the medical selection system comprising user input 110 for enabling a user to establish a selection of one or more medical images amongst a plurality of medical images 182 for establishing the one or more medical images as baseline images for use in a follow-up examination of a patient; a processor 120 for (i) generating selection data 132 being indicative of said selection, and (ii) including selection metadata in the selection data for enabling associating the selection data with the plurality of medical images; and an output 130 for providing the selection data to a medical processing system 150 for enabling the medical processing system to select, based on the selection data, the one or more medical images amongst the plurality of medical images for use as the baseline images in the follow-up examination of the patient.
Abstract:
A system includes a modeler (214) that generates a model which models a quality of findings in radiologist reports as function of deposited dose of scans from which the radiologist reports are created and a dose optimizer (216) that determines an optimal dose value for a planned scan based on the model and one or more optimization rules (218). A method includes generating a model which models a quality of fmdings in radiologist reports as a function of deposited dose of scans from which the radiologist reports are created and determining an optimal dose value for a planned scan based on the model and one or more optimization rules.
Abstract:
A training or rating system includes a shape sensing enabled device (104) and a database (140) of possible shapes and sequences of shapes for the shape sensing enabled device. The possible shapes and sequences of shapes include a collection of poses derived by appropriately performing a procedure with the shape sensing enabled device. A comparison module (154) is configured to compare real-time poses of the shape sensing enabled device with the collection of poses in the database to output comparison feedback for a user of the shape sensing enabled device.
Abstract:
A computing device (126) includes a recommender (134) that evaluates at least one of a user interaction with a displayed image of a scan of an imaging examination protocol or information about the scan in an electronically formatted radiology report, and generates a signal including a recommendation to remove the scan only in response to at least one of the user interaction or the radiology report information satisfying predetermined criteria and a output device (140) that visually presents the signal, thereby visually presenting the recommendation.
Abstract:
Methods are herein provided for decision support in diagnosis of a disease in a subject, and for extracting features from a multi-slice data set. Systems for computer-aided diagnosis are provided. The systems take as input a plurality of medical data and produces as output a diagnosis based upon this data. The inputs may consist of a combination of image data and clinical data. Diagnosis is performed through feature selection and the use of one or more classifier algorithms.
Abstract:
A system includes a modeler that generates a model which models a quality of findings in radiologist reports as a function of deposited dose of scans from which the radiologist reports are created and a dose optimizer that determines an optimal dose value for a planned scan based on the model and one or more optimization rules. A method includes generating a model which models a quality of findings in radiologist reports as a function of deposited dose of scans from which the radiologist reports are created and determining an optimal dose value tar a planned scan based on the model and one or more optimization rules.
Abstract:
A training or rating system includes a shape sensing enabled device (104) and a database (140) of possible shapes and sequences of shapes for the shape sensing enabled device. The possible shapes and sequences of shapes include a collection of poses derived by appropriately performing a procedure with the shape sensing enabled device. A comparison module (154) is configured to compare real-time poses of the shape sensing enabled device with the collection of poses in the database to output comparison feedback for a user of the shape sensing enabled device.
Abstract:
A method creates an electronically formatted schedule for imaging examinations. The method includes receiving a set of imaging examination orders, determining a protocol for each imaging examination order in the set of imaging examination orders, identifying an expected examination time duration of each of the protocols, and creating the electronically formatted schedule based on the expected examination time durations. A computing apparatus (102) includes an input device (110) that receives a set of imaging examination orders, an information extractor (202) that extracts information that determines a protocol of each imaging examination orders in the set, an expected examination duration identifier (206) that identifies an expected examination time duration of each of the protocols, and a schedule creator (220) that creates an electronically formatted schedule for the set of imaging examination orders based on the expected examination time durations.