Abstract: A medical information server receives a signal from a client device representing a first user interaction with first medical data associated with a first medical condition of a patient received from a first medical data server. A data retrieval module accesses a second medical data server to retrieve second medical data of the patient that is related to the first medical data. A data analysis module automatically performs a first analysis on image data of the first medical data to generate image quantitative result and a second analysis on the image quantitative result in view of other medical data of the patient to determine a likelihood of a second medical condition of the patient based on the analysis. A data integrator integrates the second medical data with an analysis result of the analysis to generate and transmit a view of medical information to the client device to be displayed therein.

Abstract: According to one embodiment, workflow templates are maintained, each workflow template including a predefined sequence of workflow stages associated with a particular type of medical diagnosis or process. In response to a request for processing medical image data from a user, a user identifier (ID) that identifies the user is automatically determined based on the request. At least one of the workflow templates that is specifically configured to process medical image data associated with the user is identified based on the user ID. One or more image processing operations defined by the identified workflow template are performed on the medical image data, generating a scene corresponding to an image view representing the medical image data. The scene associated with each of the workflow stages is stored in a persistent storage, where a scene includes metadata used to recreate a corresponding medical image view subsequently.

Abstract: A cloud server receives a request for accessing medical image data from a client device, where the cloud server provides image processing services to users in image processing steps, resulting in image views. User privileges of a user are determined for accessing the medical image data. In response to receiving a command having a selection of an image view from the client device, the cloud server provides the medical image data based on the selected one or more image views. The user interactions of the user with the medical image data via the selected image views are tracked, including tracking how long in time the user has spent on a particular image view. The tracked user interactions are stored in a persistent storage, and an analysis is performed on the tracked user interactions stored in the persistent storage to determine an overall usage trend of the image views.

Abstract: According to one embodiment, workflow templates are maintained, each workflow template including a predefined sequence of workflow stages associated with a particular type of medical diagnosis or process. In response to a request for processing medical image data from a user, a user identifier (ID) that identifies the user is automatically determined based on the request. At least one of the workflow templates that is specifically configured to process medical image data associated with the user is identified based on the user ID. One or more image processing operations defined by the identified workflow template are performed on the medical image data, generating a scene corresponding to an image view representing the medical image data. The scene associated with each of the workflow stages is stored in a persistent storage, where a scene includes metadata used to recreate a corresponding medical image view subsequently.

Abstract: A cloud server receives a request for accessing medical image data from a client device, where the cloud server provides image processing services to users in image processing steps, resulting in image views. User privileges of a user are determined for accessing the medical image data. In response to receiving a command having a selection of an image view from the client device, the cloud server provides the medical image data based on the selected one or more image views. The user interactions of the user with the medical image data via the selected image views are tracked, including tracking how long in time the user takes to complete a particular medical image processing step. An analysis is performed on the tracked user interactions to determine an overall usage trend of the image views.

Abstract: An automatic medical image processing system includes a series of operation stages, each automating specifying the image processing parameters for processing medical images. In response to an image processing indicator, a first medical image is automatically identified, including determining a first image operation and image processing parameters, without user intervention. The first image operation is performed on the first medical image based on the image processing parameters. A second medical image is generated and transmitted to the client device to be presented therein. The client device displays a message prompting the user whether the user is satisfied with the second medical image. In response to a user input from the client device indicating that the user is unsatisfied with the second medical image, one or more remedial options are presented to allow the user selecting a remedial action to reprocess the first medical image.

Abstract: A work flow is provided through a network. A network server receives through the network a request to convert 3D segmented medical image data to information print-ready for printing on a 3D printer or rendered for viewing. Access to converted data is limited to one or more authorized users. The 3D segmented medical image data to a converted data file. The converted data file is in a medical image data file format that allows multiple sub-segmentation of a particular human anatomy or region of interest. The medical image data file format allows for storage of mask segmentation information, color palette, shadowing, transparency and opacity.

Abstract: An artificial intelligence findings system includes an artificial intelligence findings system. An image identification engine receives new image data pertaining to a patient and past reports and image data pertaining to the patient. The image identification engine uses the past image data pertaining to the patient to identify for study images of patient anatomical structures, anatomical anomalies and anatomical features within the new image data. A findings engine receives new image data and processes the new image data to generate findings based on the new image data and based on the identified for study images of patient anatomical structures, anatomical anomalies and anatomical features within the new image data. A communication interface provides the findings to a diagnostic review system that presents the findings to a user. An adjustment engine receives notifications of changes to findings made by a user when using the medical image interpretation system.

Abstract: An artificial intelligence findings system includes a findings engine that receives medical image data and generates findings based on the medical image data and image interpretation algorithms that take into account stored preferences for a user. A client viewer presents the findings to the user. An adjustment engine allows the user to adjust the findings to produce a report. A tracking module tracks findings and adjustments made to the findings by the user when producing the report. The tracking module produces tracking information.

Abstract: A server receives a request from a client device initiated from a user operating the client device. The server determines a user action identifier (ID) based on the request, the user action ID identifying a user physical action that was captured by one or more sensors. One or more image processing commands are determined based on the user action ID in view of a first medical image currently displayed at the client device. An image processing operation is performed based on the first medical image by executing the one or more image processing commands, generating a second medical image. The second medical image is transmitted to the client device to be presented to the user at the client device.

Abstract: Image processing engines can be utilized to inject studies into other commercial or independently-developed peer review systems which are designed to review the medical findings identified by a set of physicians. Image processing engines detect, confirm or verify findings by physicians or other engines, where the engines operate as peer reviewers. The engines can prospectively “learn” from the feedback when these images are reviewed by the physicians during diagnostic interpretation creating a closed-loop quality assurance process and fostering a community platform approach to engine development which is supported by the security, governance, access control, regulatory compliance and other features of the Peer Review System. Utilizing machine learning based on the data collected from peer review, the Peer Review System can adapt and improve its performance as well as the measured performance of the physicians using the system for diagnostic interpretation.

Abstract: A server receives a request from a client device initiated from a user operating the client device. The server determines a user action identifier (ID) based on the request, the user action ID identifying a user physical action that was captured by one or more sensors. One or more image processing commands are determined based on the user action ID in view of a first medical image currently displayed at the client device. An image processing operation is performed based on the first medical image by executing the one or more image processing commands, generating a second medical image. The second medical image is transmitted to the client device to be presented to the user at the client device.

Abstract: According to one embodiment, at least a portion of medical information of a patient is displayed within MRCS executed within a local device, the medical information including medical treatment history of the patient. At least a portion of the displayed medical information of the patient is transmitted to a medical imaging processing server over a network, where the transmitted medical information includes a patient identifier (ID) of the patient. Both the at least a portion of patient medical information and one or more medical images are displayed within the MRCS, where the medical images are associated with the patient and rendered by the medical image processing server. A set of icons representing a set of image processing tools is displayed within the MRCS, which when activated by a user, allow an image to be manipulated by the imaging processing server.

Abstract: According to one embodiment, at least a portion of medical information of a patient is displayed within MRCS executed within a local device, the medical information including medical treatment history of the patient. At least a portion of the displayed medical information of the patient is transmitted to a medical imaging processing server over a network, where the transmitted medical information includes a patient identifier (ID) of the patient. Both the at least a portion of patient medical information and one or more medical images are displayed within the MRCS, where the medical images are associated with the patient and rendered by the medical image processing server. A set of icons representing a set of image processing tools is displayed within the MRCS, which when activated by a user, allow an image to be manipulated by the imaging processing server.

Abstract: A cloud server receives a request for accessing medical image data from a client device, where the cloud server provides image processing services to users in image processing steps, resulting in image views. User privileges of a user are determined for accessing the medical image data. In response to receiving a command having a selection of an image view from the client device, the cloud server provides the medical image data based on the selected one or more image views. The user interactions of the user with the medical image data via the selected image views are tracked, including tracking how long in time the user has spent on a particular image view. An analysis is performed on the tracked user interactions to determine an overall usage trend of the image views.

Abstract: A cloud server receives a request for accessing medical image data from a client device, where the cloud server provides image processing services to users in image processing steps, resulting in image views. User privileges of a user are determined for accessing the medical image data. In response to receiving a command having a selection of an image view from the client device, the cloud server provides the medical image data based on the selected one or more image views. The user interactions of the user with the medical image data via the selected image views are tracked, including tracking how much time the user takes to complete a particular medical image processing step. The tracked user interactions are stored in a persistent storage, and an analysis is performed on the tracked user interactions stored in the persistent storage to determine an overall usage trend of the image views.

Abstract: A server receives a request from a client device initiated from a user operating the client device. The server determines a user action identifier (ID) based on the request, the user action ID identifying a user physical action that was captured by one or more sensors. One or more image processing commands are determined based on the user action ID in view of a first medical image currently displayed at the client device. An image processing operation is performed based on the first medical image by executing the one or more image processing commands, generating a second medical image. The second medical image is transmitted to the client device to be presented to the user at the client device.

Abstract: A medical information server receives a signal from a client device representing a first user interaction with first medical data associated with a first medical condition of a patient received from a first medical data server. A data retrieval module accesses a second medical data server to retrieve second medical data of the patient that is related to the first medical data. A data analysis module automatically performs a first analysis on image data of the first medical data to generate image quantitative result and a second analysis on the image quantitative result in view of other medical data of the patient to determine a likelihood of a second medical condition of the patient based on the analysis. A data integrator integrates the second medical data with an analysis result of the analysis to generate and transmit a view of medical information to the client device to be displayed therein.

Abstract: An automatic medical image processing system includes a series of operation stages, each automating specifying the image processing parameters for processing medical images. In response to an image processing indicator, a first medical image is automatically identified, including determining a first image operation and image processing parameters, without user intervention. The first image operation is performed on the first medical image based on the image processing parameters. A second medical image is generated and transmitted to the client device to be presented therein. The client device displays a message prompting the user whether the user is satisfied with the second medical image. In response to a user input from the client device indicating that the user is unsatisfied with the second medical image, one or more remedial options are presented to allow the user selecting a remedial action to reprocess the first medical image.

Abstract: According to one embodiment, at least a portion of medical information of a patient is displayed within MRCS executed within a local device, the medical information including medical treatment history of the patient. At least a portion of the displayed medical information of the patient is transmitted to a medical imaging processing server over a network, where the transmitted medical information includes a patient identifier (ID) of the patient. Both the at least a portion of patient medical information and one or more medical images are displayed within the MRCS, where the medical images are associated with the patient and rendered by the medical image processing server. A set of icons representing a set of image processing tools is displayed within the MRCS, which when activated by a user, allow an image to be manipulated by the imaging processing server.