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 set of data relating to a current patient; compare the current patient set of data to a plurality of previous patient sets of data, each of the previous patient sets of data corresponding to a previous patient; select one of the previous patient sets of data based on a level of similarity between the selected previous patient set of data and the current patient set of data; and provide the selected previous patient set of data to a user.

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: The invention relates to search for cases in a database. According to the proposed method and apparatus, similarity matching is performed between an input case and a set of cases in an initial search to receive similar cases by using a given matching criterion. Then statistics on image and/or non-image-based features associated with the similar cases are calculated and presented to the user with the similar cases. In a search refinement the similar cases are refined by additional features that are determined by the user based on the statistics. The search refinement can be iterative depending on the user's need.

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 system and method of providing computer-aided analysis of medical images uses an image processor (910) to process medical image data. A decision engine (920) generates a diagnosis based on the image data (940). The decision engine estimates the probability of an illness based on the image data and assesses the relevance of any unavailable data. The result is used to request this unavailable data from the user for computing a more complete diagnosis or otherwise displaying the results in incomplete form due to either the lack of additional data or the confidence in the incomplete diagnostic results. The diagnostic results may be displayed on an output terminal (970) and may be stored in the database (930).

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 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 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 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.

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 medical selection system 100 for generating selection data includes a 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 generate selection data 132 being indicative of said selection, and includes selection metadata in the selection data for enabling associating the selection data with the plurality of medical images. An output 130 provides 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 clinical decision support (CDS) system comprises: a case grouping sub-system (10) including a graphical user interface (30) that is operative to simultaneously display data representing a plurality of patient cases and further configured to enable a user to group selected patient cases represented by the simultaneously displayed data into clinically related groups (32) as selected by the user; a probative features determination sub-system (12) that is operative to determine probative features (44) that correlate with the clinically related groups; and a CDS user interface (16) that is operative to receive current patient data relating to a current patient case and to output clinical decision support information based on values of the probative features determined from the received current patient data.

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 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: 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: 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 for suggesting autocompletion terms during text entry of a report. A text entry unit (2) for enabling a user to enter a text into a current report (1). A term selector (11) for selecting at least one frequently co-occurring term (12), based on an extracted term (8), the extracted term section (9), the current section (10), and a co-occurrence statistic (7). An indicator (13) provides an indication of the at least one frequently co-occurring term (12) to the user. A system for analyzing reports comprises a co-occurrence statistics generator (26) for generating a plurality of co-occurrence statistics, a co-occurrence statistic being indicative of a first term, a first section, a second term, a second section, and a frequency in which reports contain the first term in the first section in combination with the second term in the second section.

Abstract: A method for creating a report with an annotation includes receiving an input image to annotate. The method further includes comparing the input image with a set of previously annotated images. The method further includes generating a similarity metric for each of the previously annotated images based on a result of a corresponding comparison. The method further includes identifying a previously annotated image with a greatest similarity for each of a plurality of predetermined annotations. The method further includes visually displaying the identified image for each annotation along with the annotation. The method further includes receiving an input signal identifying one of the displayed images. The method further includes annotating the input image with the identified one of the displayed images. The method further includes generating, in an electronic format, a report for the input image that includes the identified annotation.

Abstract: This invention relates to a method and device for case-based decision support. It proposes that a case-based decision support system is trained on inputs from several radiologists in order to have a “baseline” system, and then the system provides an option to a radiologist to refine the baseline system based on his/her inputs which either refine weights of features for similarity distance computation directly or provide new similarity ground truth clusters. By enabling modifying the similarity distance computation based on user inputs, this invention adapts similarity ground truth to different users with different experience and/or different opinions.

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.