90 results about "Structured reporting" patented technology

A method and a system for analyzing a data value of interest in a multidimensional database. The data value of interest is first identified in a structured report. The data source for the structured report is retrieved. A context for the data value of interest in the data source is collected, for example, by extracting a slicer from the structured report, by extracting members of master-detail pages, or by extracting a default measure from the structured report. An analysis specification based on the collected context is then built, and the data value of interest is analyzed using the analysis specification. The result from analyzing the data value of interest may be presented in an analysis view.

The assembly and communications of a generic reporting engine for offering clinical structured reports using the Internet in an encrypted manner is provided. This method of rendering structured reports employs a DICOM Structured Reporting (SR) software database engine that maps clinical report data into a clinical structured reporting data format using a Report Editor Plug-in which is responsible for constructing the report editor GUI, for parsing the DICOM SR report to show it in the Report Editor window and to store the report content created in the GUI to the DICOM SR format. The report engine can be configured with any number of software plug-ins, so totally different ways of acquiring user input may be implemented. The current invention implements the software plug-ins using a tree-like GUI. The current implementation of this plug-in is based on DICOM SR pull model which is considered more feasible to control its presentation form, but the reporting engine allows for implementation of push model report editor plug-ins. Nothing in this novel approach to clinical reporting prevents the application from implementing a report editor from editing any DICOM SR report in a generic way, like recognizing a report from voice dictation. The Reporting Engine of the present invention provides a way for the plug-ins to recognize if they are able to open the report or not. It can be done either by software plug-ins' report introspection or the process is configurable in the using the invention's reporting engine. The novel reporting engine provides a way of configuring a Report Editor Plug-in, so with one generic plug-in one may have many report templates just by configuring the plug-in. The currently implemented plug-in uses this possibility to define the report definition and GUI tree in a configuration file.

Methods and systems of creating and sharing structured reports. In one embodiment, a system for creating structured reports includes a business logic server and a structured object repository configured to hold at plurality of structured report templates. The structured report templates are based on a common schema. The system also includes at least one inbound message device configured to receive data from at least one source of patient data in a message-oriented protocol, to convert the data from the at least one source of patient data to a format recognized by the business logic server, and to send the converted data to the business logic server. The business logic server may be configured to obtain the at least one structured report template and to create a structured report by inserting the converted data into the at least one structured report template.

Methods, frameworks and systems for validating DICOM (Digital Imaging and Communications in Medicine) SR (Structured Reporting) XML (Extensible Markup Language) documents against DICOM SR templates, using XSLT (Extensible Stylesheet Language Transformations) technology alone or as a complement to XML Schema, are disclosed. A framework of generating XSLT stylesheets from XML representation of DICOM SR templates is developed. Also a mechanism and method of automatic generating XSLT stylesheets for validating SR document contents are provided. In addition, a mechanism and method of flexibly adapting in different DICOM SR XML formats is provided.

The invention enables multimodal cognitive communications, collaboration, consultation and instruction between and among heterogeneous networked teams of persons, machines, devices, neural networks, robots and algorithms during various stages of medical disease management, including detection, diagnosis, prognosis, treatment, measurement, monitoring and reporting. The invention enables both synchronous and asynchronous multiparty collaboration with multichannel, multiplexed streaming imagery data, including interactive curation, multisensory annotation and metadata tagging, as well as multi-formatted encapsulation, saving and sharing of collaborated imagery data as packetized augmented intelligence. The invention acquires both live stream and archived medical modality imagery from network-connected medical devices, cameras, signals and sensors, as well as multiomic data [phenotypic, genomic, metabolomic, pathomic, radiomic, radiopathomic and radiogenomic] maps and clinical data sets from structured reports and clinical documents, including biometric maps and movies, hapmaps, heat maps and data stream visualizations. The invention also acquires both medical and non-medical streaming imagery data from image data repositories, documents and structured reports, workstations and mobile devices, as well as from wearable computing, signals and sensors. The invention enables networked teams to interactively communicate, concurrently collaborate and bi-directionally exchange multichannel multiplexed imagery data streams, singly or together, in real time or asynchronously, generally by curating, annotating and tagging imagery information objects. The invention encapsulates and saves collaborated imagery data, together with multisensory annotations and metadata tags, in standard file formats as packetized augmented intelligence. The invention enables recursive cognitive enrichment of clinical cognitive vismemes, and saves packetized imagery information objects, multisensory annotations and metadata tags in native file formats [PDF, MPEG, JPEG, XML, XMPP, QR,TIFF, RDF, RDF/XML, SVG and DAE] as well as in formats compliant with standards for digital communications in medicine [DICOM]. The invention enables live stream multicasting of multimodal cognitive instruction and collaborative knowledge exchange with multisensory [visual, auditory, haptic] annotation of streaming imagery data, as well as secure, encrypted transmission of streaming augmented intelligence across file sharing data networks for informatics-enabled learning, specialist skills acquisition and accelerated knowledge exchange.

Certain examples provide systems, apparatus, and methods to facilitate automated processing of report text to associate text with external content to be accessed via the report. An example method includes automatically processing report text according to natural language processing of the text to identify a text element in the report associated with content external to the report. The example method includes associating the identified text element in the report with a link to the identified content external to the report to structure the report with reference to the external content. The example method includes providing the structured report for access and manipulation by a user.

A method and system which may be used to display a number of computer-detected regions of pathological interest using interactive CAD markers are presented. In one embodiment, a layer of uniquely identified CAD markers corresponding to computer-detected regions of pathological interest of an anatomical feature may be simultaneously displayed with an image of the anatomical feature. Each individual CAD marker may be configured to incorporate viewable classification data entered by a user and may further be configured to visually indicate the probability of cancer determined by the CAD algorithm. Each individual CAD marker and the information associated therewith may also be saved with the image such that it may be incorporated into, for example, a structured reporting system.

A system uses a flexible mapping capability in adaptively exchanging image related data between a structured report data format and data formats employed by different types of image processing device. A system provides medical image associated measurement data from different types of imaging device in a particular report format data structure. The system includes an acquisition processor for acquiring measurement data associated with medical images produced by an examination of a particular patient using a particular type of imaging device. A repository of mapping information associates clinical terms used by multiple different types of imaging device with corresponding codes compatible with a particular report format data structure employed for providing an imaging examination report of a particular patient. A data processor uses the repository in converting clinical terms in the acquired measurement data provided using the particular type of imaging device to corresponding codes compatible with a particular report format data structure. The data processor processes the codes corresponding to the converted clinical terms as well as elements of the acquired measurement data for incorporation in the particular report format data structure.

The invention relates to a head medical image auxiliary interpretation structured report generation method based on a neural network. According to the method, the interpretation of the brain image andthe generation of the structured report can be completed in a full-automatic manner; the workload of a user is greatly reduced; the focus can be modified through manual intervention so as to improvethe accuracy; wherein the interpretation process is completed by stages; according to the method, the quality of each stage is guaranteed to be controllable. Meanwhile, corresponding interpretation models and structured reports are used for different image types and different disease types, compared with a report directly generated through images, the target is clearer, the result is more accurate, interpretability is higher, and the automatically generated report is more standard and objective and can be used for cultivating doctors with insufficient experience; the structured report is presented in a Key/Value form and stored in a JSON format, so that the report is convenient for doctors to modify, and the lightweight data format is convenient for storage and transmission.

A system generates structured compliance form data based on a compliance form having a plurality of data fields. The system includes multiple parsing modules each configured to generate respective parsed form data by analyzing compliance form data related to the compliance form with respective parsing processes. The system includes a combiner module configured to combine the various parsed formed data into combined parsed form data.

Certain embodiments of the present invention provide a system and method for structuring dynamic data from a plurality of images. Certain embodiments include accessing an image data set including data representing a plurality of images, determining a dynamic or functional attribute in the image data set, associating the dynamic or functional attribute with a lexical attribute from a lexicon, and storing the lexical attribute and an associated code. The lexical attribute and associated code may be stored in a database and/or a structured report, for example. The lexicon may be modified to accommodate attributes and medical terminology. Attributes relate to a feature and/or a region of interest in the image data set.

The invention discloses a CT (computed tomography) tuberculosis testing artificial intelligence diagnosis and treatment system which comprises a feature sample library, a neuron network learning module, a deep convolutional neural network learning module, an output module and a computer terminal, and a large number of samples capable of being learned by the neuron network learning module and the deep convolutional neural network learning module are arranged in the feature sample library. The system is novel in design, the neuron network learning module and the deep convolutional neural networklearning module can deep learn marked images in the feature sample library by the aid of a pulmonary nodule artificial intelligence diagnosis and treatment system to obtain accurate pulmonary noduleclassification strategy, pulmonary nodules are detected, the sizes, the shapes and benign and malignant properties of the nodules are judged, a structured report is automatically made for reference ofdoctors, so that intelligent film reading and auxiliary diagnosis and treatment functions based on pulmonary nodule images are provided for the doctors, and diagnosis and treatment suggestions are offered for the doctors.

The invention provides a method for calculating intracerebral hemorrhage amount based on depth learning, which comprises the following steps: S1, obtaining CT image data of intracerebral hemorrhage and marking; S2, designing a segmentation model of an intracerebral hemorrhage region based on depth learning, and training the segmentation model by using the marked intracerebral hemorrhage CT image data; S3, inputting the tested CT image data of cerebral hemorrhage into the trained segmentation model to obtain the segmentation result; S4, calculating the volume of cerebral hemorrhage according tothe obtained segmentation result; S5: generating a structured report containing the location and volume of intracerebral hemorrhage. The invention can accurately and quickly calculate the amount of cerebral hemorrhage, and provides important decision information for clinical intervention.

The invention provides a cloud labeling system, which comprises a data management module, a focus intelligent extraction module, an artificial intelligence diagnosis and prediction module, a structural report module and an application basic framework module. The data management module is established by downloading data from a known database. The focus intelligent extraction module is used for carrying out automatic labeling training through data in the data management module, acquiring data from a plurality of hospitals, and verifying an automatic labeling algorithm by using the data of the plurality of hospitals. The artificial intelligence diagnosis and prediction module is used for detecting focus in the data marked by the automatic labeling algorithm, and automatically judging symptomsin the data. The structural report module is used for extracting focus and symptoms, and forming a marked record file. The application basic framework module is used for bearing the data management module, the focus intelligent extraction module, the artificial intelligence diagnosis and prediction module and the structural report module.

The invention provides a system for automatically generating an image structured report template. The system comprises a data storage module for storing all elements of the structured report templateof all diseases, focus attributes corresponding to all the elements and hierarchical relationships between all the elements; a generation module which generates editable logic elements according to the elements and the focus attributes, wherein the types of the logic elements include single selection, multi-selection, edit boxes, large edit boxes, single selection with edit boxes, multi-selectionwith edit boxes, pages, labels, areas, key images and sub-applications; and an interface layout module which determines the positions and sizes of the logic elements on the structured report interfaceaccording to the hierarchical relationship, the types of the logic elements and the focus attributes, and forms the structured report interface based on the positions and sizes of the logic elements.The invention further discloses a method for automatically generating the image structured report template. According to the method, the threshold and difficulty of manufacturing the structured template are reduced, and the efficiency of editing the structured report is improved.

An informatics platform provides an architecture to integrate information from relevant patient information systems. The informatics platform may include: a workflow tool that can be used to prepare and review information at multi-disciplinary board meetings; a visual timeline of patient events; a search engine to search for patients with specific attributes; a graphing tool that can display disparate clinical variables in a single chart; a virtual Pin Board for users to identify relevant patient information for board meetings; an image viewing application that can provide for comparison of images from different information systems; structured reporting functionality that incorporates system aggregated patient information and board recommendations; an application interface that integratesclinically relevant tools to provide patient specific references; a collaboration interface that facilitates communication of patient specific information and documents the discussion threads as independent reference points; and a default display of relevant patient information customized for each clinical specialty.

A medical image aided diagnosis method and system combining image recognition and report editing. The medical image aided diagnosis method comprises the following steps S1, establishing an image semantic expression knowledge graph of medical images, S2, obtaining a medical image of a patient, determining a region of interest on a two-dimensional image, and providing a candidate focus option of the patient according to the image semantic expression knowledge graph and the region of interest; and S3, determining a focus type according to the region of interest and the candidate focus option; performing division to obtain a lesion region according to the focus type, and generating a structured report related to a region-of-interest of the medical image of the patient, and adding the lesion region and corresponding expression content of image semantics into a corresponding focus image library. In the method, medical image recognition is performed by combining an image semantic expression knowledge graph and a variety of machine leaning, sample images can be deeply accumulated, the image semantic expression knowledge graph can be continuously improved, and aided diagnosis capabilities of medical images can be enhanced.

The invention discloses a medical image report information extraction method and device, equipment and a storage medium, and relates to the technical field of computers. The method comprises the steps of obtaining text information of a medical image report; performing encoding processing on a word sequence in the text information to obtain a word vector corresponding to the word sequence, the word vector being fused with a semantic relationship between context words in the word sequence; carrying out entity information extraction on the word vectors to obtain a structured report text corresponding to the medical image report, the structured report text comprising entities contained in the text information and entity types to which the entities belong. By performing entity information extraction on the medical image report, a structured report text can be generated, writing habits of medical staff are reserved, and universality is achieved.