Abstract: When evaluating patient cases to determine complexity thereof, a computer-aided stratification technique is applied to analyze historical patient case diagnoses and correctness thereof in order to calculate a stratification score (20) for each of a plurality of abnormality types and/or anatomical locations. When a new patient case is received, the computer-aided stratification technique is applied to evaluate the patient case in view of historical data and assign a stratification score thereto. A ranked list (21) of current patient cases can be generated according to stratification scores, and physician workload can be adjusted as a function thereof so that workload is balanced across physicians and/or according to physician experience level.

Abstract: A magnetic resonance imaging scan using a MR scanner receives via a user interface a MR imaging protocol categorizable into a MR scan type of a predefined set of MR scan types. Further, a database is queried by providing to the database scan information permitting the database to identify the MR scan type of the MR imaging protocol. Statistical information on the MR scan type which can include statistics on modifications of individual scan parameters of the MR scan type is received from a database, and the statistical information is provided to the user interface. Modifications of the MR imaging protocol can be received from the user interface, resulting in a modified MR imaging protocol, according to which the MR imaging scan can be performed.

Abstract: A method includes obtaining, in electronic format, an image (102) including a medical image display region (104) and an information display region (106). The at least one of the medical image display region or the information display region includes graphical indicia representing at least one of an annotation (110, 112, 114, 116) or alphanumeric information (118, 120, 122, 124, 126, 128, 130, 132, 134, 136, 138, 140). The method further includes evaluating pixels of the image to identify pixels including the graphical indicia representing an annotation or alphanumeric information of interest in the image. The method further includes extracting the annotation or alphanumeric information of interest from the identified graphical indicia from the image. The method further includes inserting the extracted annotation or alphanumeric information of interest in an electronically formatted clinical report for the image.

Abstract: A healthcare decision support system for tailoring patient care comprises a processor and a computer-readable storage medium, wherein the computer-readable storage medium contains instructions for execution by the processor causing the processor to perform the steps of obtaining media stimulation and feedback data of a patient in an adaptive healing environment, said media stimulation and feedback data including information on interactions of the patient with the adaptive healing environment, obtaining condition data of the patient, obtaining electronic health record data of the patient, evaluating the obtained data and determining a patient parameter including information on the patient set and providing the patient parameter set to a medical decision support component. The present invention further relates to a corresponding method and to a patient care system.

Abstract: A method includes obtaining electronically formatted information about previously performed imaging procedures, classifying the information into groups of protocols based on initially selected protocols for the previously performed imaging procedures and generating data indicative thereof, identifying deviations between the classified information and the corresponding initially selected protocols for the previously performed imaging procedures, and generating a signal indicative of the deviations. A method includes recommending at least one of a plurality of protocols for an imaging procedure based on at least one of a score, a probability, or a pre-determined rule, which is based on extracted medical concepts from patient information and extracted medical concepts from previously imaged patient information, and generating a signal indicative of the recommendation.

Abstract: A robotic control system employs a robot unit (10) and a control unit (20). The robot unit (10) includes an endoscope (12) for generating an endoscope image (14), and a robot (11) for moving the endoscope (12) within an anatomical region. The control unit (20) includes an endoscope controller (22) for a determination of an endoscope pose within the anatomical region for an intraoperative visualization of the anatomical feature within the endoscope image (14), wherein the endoscope path is derived from a delineation of a volume coordinate position of the anatomical feature within a pre-operative image (43) of the anatomical region. The control unit (20) further includes a robot controller (21) for commanding the robot (11) to move the endoscope (12) to the endoscope pose within the anatomical region to visualize the anatomical feature within the endoscope image (14).

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: 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 classifier (20) is trained by a feature matrix (18, 18?) made up of feature vectors (F11, . . . , Fkm). The feature vectors are generated by operating on each of a plurality (k) of training image data sets with each of a plurality (m) of image processing algorithms (121, . . . , 12m) to generate processed and segmented images. Features of the segmented regions are extracted (14) to generate the feature vectors. In this manner, the classifier is trained with data generated with a variety of image processing algorithms.

Abstract: A non-transitory computer-readable storage medium storing a set of instructions executable by a processor. The set of instructions is operable to receive a current patient medical image of a current patient, compare the current patient medical image to a plurality of previous patient medical images, each of the previous patient medical images corresponding to a previous patient, select one of the previous patients based on a geometric similarity between the previous patient medical image of the selected one of the previous patients and the current patient medical image, and determine an initial radiation treatment plan based on a radiation treatment plan of the selected one of the previous patients.

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 and method for generating summary data based on a patient report. The method includes receiving at least one patient report of a plurality of patient reports. The patient report includes first data relating to a patient. The method also includes analyzing the at least one patient report to identify at least one section as a function of predetermined identifiers. The method also includes analyzing the at least one section to identify second data relating to the patient. The method also includes generating summary data as a function of the identified second data.

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.

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: 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 method for identifying relevant follow-up recommendations from medical reports includes identifying with a processor follow-up recommendations in electronically formatted prior medical reports, and visually presenting, via a display monitor, the identified follow-up recommendations. A computing apparatus (102) including a processor that obtains, in electronic format, an imaging examination order for a follow-up imaging examination of a patient, wherein the imaging examination order at least includes a unique identification of the patient, retrieves electronically formatted prior medical reports of the patient from a data repository based on the patient or the unique identification of the patient, identifies follow-up imaging recommendations in the retrieved electronically formatted prior medical reports, and visually presents the identified follow-up imaging recommendations.

Abstract: A method includes obtaining image data for a patient. The image data corresponds to acquisition data from an imaging acquisition from a set of planned image acquisitions in an examination plan for the patient. The method further includes analyzing the image data with a processor based on an imaging practice guideline and producing electronically formatted data indicative of the analysis. The processor generates a signal indicative of a recommendation of a change to the examination plan based on the data indicative of the analysis.

Abstract: A method includes obtaining electronically formatted information about previously performed imaging procedures, classifying the information into groups of protocols based on initially selected protocols for the previously performed imaging procedures and generating data indicative thereof, identifying deviations between the classified information and the corresponding initially selected protocols for the previously performed imaging procedures, and generating a signal indicative of the deviations. A method includes recommending at least one of a plurality of protocols for an imaging procedure based on at least one of a score, a probability, or a pre-determined rule, which is based on extracted medical concepts from patient information and extracted medical concepts from previously imaged patient information, and generating a signal indicative of the recommendation.

Abstract: A method includes identifying medical concepts in identified patient cases that are missing from medical concepts in first electronically formatted medical information as missing medical concepts, and selecting an imaging protocol for an imaging procedure based on a combination of the medical concepts from the first electronically formatted medical information and the missing medical concepts, and generating a signal indicative of the selected imaging protocol. A method includes identifying at least one of one or more medical concepts as a relevant additional concept, and selecting an imaging protocol for the imaging procedure based on a combination of one or more clinical indications and the relevant additional concept, and generating a signal indicative of the selected imaging protocol.