Abstract: A radiology workstation (16) includes a display device (25) and at least one user input device (20, 22, 24). A server computer (10) is programmed to operate with the radiology workstation to perform the radiology reading task (14) including a radiology reading support method comprising: receiving user input identifying a radiological finding; retrieving a structured finding object (SFO) template for the radiological finding; displaying an SFO annotation graphical user interface (GUI) dialog (40) having annotation data entry fields for annotating the retrieved SFO template; building an SFO (60) representing the radiological finding by annotating the SFO template via the SFO GUI dialog; and generating natural language text describing the radiological finding from the SFO. Application program interface (API) action rules (54) may be applied to determine whether the SFO being built satisfies any API action rule, and if so a corresponding application program is invoked.

Abstract: A system and method for analyzing a patient report to determine whether a follow-up has been recommended. The system and method perform the steps of extracting a portion of text indicating a follow-up recommendation from the report, extracting a name of the follow-up recommendation and determining a corresponding time interval from the portion of text, extracting context information relating to the patient report, and determining, based on the context information and the name of the follow-up recommendation, whether an appointment corresponding to the follow-up recommendation has been scheduled.

Abstract: A system for providing actionable annotations includes a clinical database storing one or more clinical documents including clinical data. A natural language processing engine which processes the clinical documents to detected clinical data. A context extraction and classification engine which generates clinical context information from the clinical data. An annotation recommending engine which generates a list of recommended annotations based on the clinical context information. A clinical interface engine which generates a user interface displaying the list of selectable recommended annotations.

Abstract: A system for creating a longitudinal view of patient findings includes a natural language processing engine which extracts clinical findings from a clinical document. A temporal resolution engine determines which other clinical documents the clinical findings belong to. A visualization graphical user interface indicates the correlation of the clinical findings between the clinical document and the other clinical documents. The natural language processing engine also links one or more images to the clinical findings.

Abstract: A system for generating a patient clinical history for a current exam includes a clinical information database containing one or more clinical documents. Each clinical document including a list of patient specific information items. A clinical information crawler engine queries the clinical information database for clinical data, the clinical data including one or more information items. A clinical history construction interface displays the clinical data to the user. A narrative construction engine concatenates information items within the clinical data selected in the clinical history construction interface by the user and creates a free-text rendering, wherein the free-text rendering is inserted into the patient clinical history of a clinical report.

Abstract: Described herein are systems and methods for intelligently combining medical findings received across different modalities. The system comprises an extraction module extracting contextual information from an image of an area of interest including annotations, a feature selection module building a current feature vector using the extracted contextual information and the annotations, and a referencing engine computing a similarity score between the current feature vector and a prior feature vector of a prior image. The method comprises extracting contextual information from an image of an area of interest including annotations, building a current feature vector using the extracted contextual information and the annotations, and computing a similarity score between the current feature vector and a prior feature vector of a prior image.

Abstract: A device and method integrates a lesion stager in a reporting tool. The method includes receiving a user input. The user input is image data including at least one variable value. The variable value is indicative of a variable parameter of the image data. The method includes associating each of the at least one variable value with a corresponding variable parameter to generate at least one variable-value pair. The method includes determining a computed output value as a function of select ones of the at least one variable-value pair.

Abstract: A text analysis system is described. A natural language input unit (1) is arranged for enabling a user to input a free text (10) in a natural language. A natural language processing unit (2) is arranged for processing at least a portion of the free text (10) while it is being inputted, to obtain an explicit representation (11) of semantics represented by the free text. An explicit information input unit (3) is arranged for enabling the user to input explicit information (12) relating to the explicit representation (11) of semantics. The system comprises a visualization unit (4) for visualizing at least part of the explicit representation (11) to the user while the user is still inputting the free text (10). A user interface (5) is arranged for providing a user with simultaneous access to both the natural language input unit (1) and the explicit information input unit (3).

Abstract: A system for grouping image annotations is disclosed. A display unit (1) is arranged for displaying a plurality of medical images relating to a subject (5) comprising a representation of an anatomical object. An annotation unit (2) is arranged for receiving information regarding input of a plurality of annotations (3) of the plurality of medical images via a user interface (4), wherein each annotation comprises geometric information relative to an image of the plurality of medical images. A grouping unit (4) is arranged for detecting a group of annotations among the plurality of annotations, based on the geometric information and a set of rules that define general properties of geometric relationships of annotations (3) that belong to the same object. The detecting of the group of annotations is further based on a geometric relationship between the plurality of medical images.

Abstract: A system for selecting a set of documents from a health record of a patient (1) is disclosed. A specialty unit (21) is arranged for determining a specialty (3) for selecting the set of documents, to obtain a determined specialty. A first selecting unit (4) is arranged for selecting a first set of documents (5) from the health record, wherein a specialty of a physician associated with the documents of the first set of documents (5) matches the determined specialty. A body part determining unit (6) is arranged for determining a body part (7) associated with at least one document of the first set of documents (5), to obtain a body part. A second selecting unit (8) is arranged for selecting a second set of documents (9) from the health record, wherein a body part associated with the documents of the second set of documents matches the determined body part.

Abstract: An annotation support system (10) comprising at least one display device (20). A context extraction module (24, 36) determines a context of a current medical image from a current image study. A matching module (26, 38) compares the context of the current medical image to contexts of prior medical images from prior image studies. A display module (28, 40) displays at least one of context relevant annotations and context relevant medical images from the prior image studies which match the context of the current medical study.

Abstract: A system for detecting and visualizing finding-specific suggestion and information includes a clinical database storing one or more clinical documents including clinical data. A natural language processing engine processes the clinical documents to detect clinical data pertinent to a patient. A context extraction and classification engine extracts clinical findings from the clinical data and detects finding-specific suggestions from the clinical findings. A clinical interface engine generates a user interface which enables the user to view the detected clinical data and finding-specific suggestions.

Abstract: The invention relates to a system (100) for classifying image data on the basis of a model for adapting to an object in the image data, the system comprising a segmentation unit (110) for segmenting the image data by adapting the model to the object in the image data and a classification unit (120) for assigning a class to the image data on the basis of the model adapted to the object in the image data, thereby classifying the image data, wherein the classification unit (120) comprises an attribute unit (122) for computing a value of an attribute of the model on the basis of the model adapted to the object in the image data, and wherein the assigned class is based on the computed value of the attribute. Thus, the system (100) of the invention is capable of classifying the image data without any user input. All inputs required for classifying the image data 10 constitute a model for adapting to an object in the image data.

Abstract: A document creation system is disclosed. A text input unit (1) is arranged for receiving an input from a user for inclusion into a document (10) as text (11). A selection input unit (2) is arranged for receiving a user selection of a macro (15), wherein the macro comprises a text portion (16) and structured semantic information (17) relating to the text portion (16). A text inserter (3) is arranged for inserting the text portion (16) into the document (10), in response to the user selection. An annotation unit (4) is arranged for annotating the document (10) with an annotation (12) based on the structured semantic information (12). The text portion (16) of a macro (15) can comprise a blank to be filled in. A field input unit (6) is arranged for receiving from the user at least one value associated with said at least one blank.

Abstract: Extensive databases of well-annotated reports are important knowledge sources in medical workflows, such as in radiology. These are typically accessed by the healthcare professional looking for reports similar to a current case being evaluated. However, filling and maintaining such databases requires considerable effort. A system is provided for storing a candidate report, comprising a searcher configured to retrieve one or more queries from a query database; to retrieve the candidate report from a user input; to execute the one or more queries on the candidate report to determine the relevance of the candidate report, and to store the candidate report in the report database if the relevance exceeds a predetermined value. This provides a check, prior to storing, to evaluate whether a candidate report would actually be a worthwhile addition to the database. If not, it is by default not added.

Abstract: A text analysis system is described. A natural language input unit (1) is arranged for enabling a user to input a free text (10) in a natural language. A natural language processing unit (2) is arranged for processing at least a portion of the free text (10) while it is being inputted, to obtain an explicit representation (11) of semantics represented by the free text. An explicit information input unit (3) is arranged for enabling the user to input explicit information (12) relating to the explicit representation (11) of semantics. The system comprises a visualization unit (4) for visualizing at least part of the explicit representation (11) to the user while the user is still inputting the free text (10).

Abstract: A system for processing a report, comprising a natural language processing unit (1) for processing a natural language textual report to detect a description of a reference to at least part of a data object, wherein the description is expressed in natural language as a part of the natural language textual report. The system comprises an accessing unit (2) for accessing said at least part of the data object in a collection of data objects, based on the reference. The system comprises an associating unit (3) for associating the accessed at least part of the data object with the description of the reference. The natural language processing unit (1) comprises a view parameter extraction unit (4) for extracting a view parameter indicative of a view of the data object from the description of the reference.

Abstract: A system for processing at least one document (7) comprising a text, wherein the system comprises an associating unit (1) arranged for associating a first part of said at least one document with a second part of said at least one document, based on a similarity of semantic data associated with text comprised in the first part and semantic data associated with text comprised in the second part. A semantic data generator (2) is arranged for generating semantic data associated with at least part of the text, wherein the semantic data comprises an explicit representation of semantic information expressed by at least part of the text. A selector (3) is arranged for enabling a user to select the first part of the document.

Abstract: A system for generating a view of a medical image comprises an input (1) for receiving information indicative of a suspected diagnosis of a patient. An input (2) for receiving a medical image of the patient. A mapper (3) for mapping the suspected diagnosis of the patient to a set of viewing parameters for viewing the medical image. A view generator (8) for providing a view of the medical image in accordance with the set of viewing parameters. A database (4) for mapping a suspected diagnosis into a set of generic viewing parameters. A transformer (5) for transforming the set of generic viewing parameters into a set of image-specific viewing parameters based on content of the medical image.

Abstract: A system and method for presenting summarized information of medical reports. The system and method receiving a plurality of medical reports, each medical report including a plurality of sections, each of the sections including text content, correlating corresponding sections of each of the medical reports into section types, extracting the text content of the sections of the medical reports for a selected section type and aggregating, into a single display, the text content of the sections of all the medical reports for the selected section type.