Abstract: A region of interest (ROI) segmentation system (10) includes a display device (20), a gaze-tracking device (28), a gaze point collector (32), a boundary identifier(36), and a region identifier (38). The display device (20) displays an image (14). The gaze-tracking device (28) generates gaze points relative to the displayed image (14). The gaze point collector (32) selects gaze points from the generated gaze points (30) corresponding to a region of interest (ROI) (25) of the displayed image (14). The boundary identifier (36) estimates a boundary (70) based on the selected gaze points (54, 60). The region identifier (38) segments the ROI (25) based on the estimated boundary (70).

Abstract: A system includes (100) includes a display (112) that sequentially displays images from an image data set at a predetermined rate, an optical attention monitoring device (120) that senses a characteristic indicative of a clinician's attention to each displayed image of the image data set, and a processor (106) that executes an attention detection module (118) that detects a lapse in attention with respect to one or more of the displayed images based on the sensed characteristic indicative of the clinician's attention and generates a signal indicating the one or more of the displayed images.

Abstract: A system and method for receiving a plurality of reports, each of the reports describing a corresponding one of a plurality of medical imaging studies of a patient, extracting, from each of the reports, a corresponding characteristic, identifying a subset of the reports based on a similarity of the characteristics of the reports comprising the subset and generating a visualization of a portion of a patient history for the patient, the portion comprising the subset of the reports.

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 medical image navigation system (2) includes a viewport module (4), a proximity module (26), a visualization module (28) and a matching module (34). The viewport module (4) navigates a plurality of image slices of a study and based on input from at least one input device selects at least one image which is displayed and any annotations associated with the selected at least one image on a display device. The proximity module (26) for the selected image slice returns at least one proximate annotation, if available. The visualization module (28) for the returned at least one proximate annotation visualizes the at least one proximate annotation which is displayed by the viewport module on the selected at least one image. A matching module (34) retrieves for display an image slice in one study which corresponds to a displayed image slice from another study.

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 and method for automatically setting image viewing context.

Abstract: A system, method and computer readable storage medium for analyzing a medical report to determine if interval change data corresponding to a change of the medical data over time is required, extracting keywords from a predetermined field in the medical report corresponding to an interval change, categorizing the extracted keywords into a first category corresponding to the interval change if the keywords conform to a first pattern and categorizing the extracted keywords into a second category if the keywords conform to a second pattern and generating a notification message if the keywords correspond to the second category.

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: A system for correlating patient radiology and pathology reports to track discordance among radiology and pathology diagnoses includes a natural language processor engine which extracts radiological information and pathology information. A correlation module correlates the radiology information and pathology information in a specific time period. A visualization graphical user interface indicates the correlation of radiology information and pathology information in a patient history. A tracking module which tracks misdiagnosis cases.

Abstract: When automatically populating medical report templates, insertable macros are indexed and searched not only my name or title but also by contents, such as keywords times, pre-defined terms for key information included in the macro, free texts in the macros, etc. When a unique macro is found, the system inserts the text of the macro into the report being generated. If multiple related macros are found, the system highlights the macros for user review. After the insertion of the macro into the template, the system identifies pre-defined terms and fills in the key information value(s). The system thus facilitates, e.g., radiologists' observation reporting procedure through an intelligent matching algorithm that facilitates finding a comprising keywords unique macro, which in turn aids in filling in report field instance values and optimizes radiology workflow.

Abstract: As medical imaging becomes more affordable, and the diversity of diagnostic modalities and therapeutic treatments increase, the amount of data being stored increases, and the problem becomes even more critical. One approach to improve retrieval efficiency of images is to employ semantics to establish a defined set of search and classification terms. However, such semantic systems still require the user to make a selection of the most appropriate term or terms to classify a report or image, and the accuracy of the results are thus dependent on the skill and knowledge of the classifier. According to a first aspect of the invention, a retriever is provided for retrieving a medical image having a searchable attribute, the retriever being configured to interface with a semantic database and an image database, and wherein the searchable attribute is determined by segmenting the medical image, using the anatomical model.

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 method includes detecting a focus of attention of an observer of an anatomical image of a set of images, determining a location of the anatomical image includes tissue with a finding of interest based on the detected focus of attention, identifying an anatomical image, from an earlier acquired imaging data set, with a same portion of tissue as the displayed image, visually displaying graphical indicia, concurrently with the displayed image, that identifies the earlier acquired image.

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 (100) for enabling study of image data, comprising:—a user interface subsystem (120) for i) receiving navigation commands (022) from a user, and ii) displaying different views (400) of the image data (042) in response to the navigation commands for enabling the user to navigate through the image data;—a function execution subsystem (160) for executing individual ones of a plurality of system functions (500) to support the user in the study of the image data; and—a pattern analysis subsystem (140) for: j) obtaining, from the user interface subsystem, data (022) indicative of a display sequence of the different views during the navigating through the image data, jj) analyzing the data to determine a navigation pattern (631) of the user, and jjj) based on the navigation pattern, selecting one of the plurality of system functions for execution by the function execution subsystem.

Abstract: A system and method for automatic segmentation, performed by selecting a deformable model of an anatomical structure of interest imaged in a volumetric image, the deformable model formed of a plurality of polygons including vertices and edges, displaying the deformable model on a display, detecting a feature point of the anatomical structure of interest corresponding to each of the plurality of polygons and adapting the deformable model by moving each of the vertices toward the corresponding feature points until the deformable model morphs to a boundary of the anatomical structure of interest, forming a segmentation of the anatomical structure of interest.

Abstract: A system, method and computer readable storage medium for generating a context driven summary view of medical findings by retrieving a current study including at least one image to be analyzed, extracting current context information from the current study and storing the current context information in a database and matching the current context information with prior context information from prior studies to return a set of relevant prior studies.