Abstract: A generalized distributed framework is provided for parallel search and retrieval of unstructured and structured patient data across zones with hierarchical ranking. In various embodiments, patient data is ingested from a plurality of data sources. A plurality of data models is populated based on the ingested patient data, each data model comprising an abstract data type. The plurality of data models is stored in an index. A search request is processed against the index, the search request comprising one or more attribute of the abstract data type.

Abstract: Annotation of large image datasets is provided. In various embodiments, a plurality of medical images is received. At least one collection is formed containing a subset of the plurality of medical images. One or more image from the at least one collection is provided to each of a plurality of remote users. An annotation template is provided to each of the plurality of remote users. Annotations for the one or more image are received from each of the plurality of remote users. The annotations and the plurality of medical images are stored together.

Abstract: Annotation of large image datasets is provided. In various embodiments, a plurality of medical images is received. At least one collection is formed containing a subset of the plurality of medical images. One or more image from the at least one collection is provided to each of a plurality of remote users. An annotation template is provided to each of the plurality of remote users. Annotations for the one or more image are received from each of the plurality of remote users. The annotations and the plurality of medical images are stored together.

Abstract: Embodiments of the present invention relate to discriminating between normal and abnormal left ventricles in echocardiography. In some embodiments, a first region of a first image of a heart is located by clustering. The first region depicts a chamber of the heart. The chamber has a chamber shape. A boundary of the first region is determined by contour tracing a retaining the traced contour overlapping the first region. A predetermined shape is compared to the boundary. The predetermined shape had been determined without reference to the first image. A first plurality of parameters is determined that, when applied to the predetermined shape, conforms the predetermined shape to the boundary and minimizes at least one error between the predetermined shape and the boundary. An indication of normality or abnormality is determine from the first plurality of parameters.

Abstract: A generalized distributed framework is provided for parallel search and retrieval of unstructured and structured patient data across zones with hierarchical ranking. In various embodiments, patient data is ingested from a plurality of data sources. A plurality of data models is populated based on the ingested patient data, each data model comprising an abstract data type. The plurality of data models is stored in an index. A search request is processed against the index, the search request comprising one or more attribute of the abstract data type.

Abstract: Automatic detection of disease from analysis of echocardiographer findings in echocardiogram videos is provided. In various embodiments, a plurality of medical images containing embedded text are read. The plurality of medical images are clustered into a plurality of clusters. Medical images of a first cluster of the plurality of clusters are ranked based on the frequency of measurement names within the medical images of the first cluster. A candidate tabular template is generated indicative of a layout of measurement name/value pairs within the medical images of the first cluster. According to the candidate tabular template, optical character recognition is applied to one of the plurality of medical images of the first cluster to extract candidate measurements. The candidate tabular template and the candidate measurements are presented to a user.

Abstract: Annotation of large image datasets is provided. In various embodiments, a plurality of medical images is received. At least one collection is formed containing a subset of the plurality of medical images. One or more image from the at least one collection is provided to each of a plurality of remote users. An annotation template is provided to each of the plurality of remote users. Annotations for the one or more image are received from each of the plurality of remote users. The annotations and the plurality of medical images are stored together.

Abstract: Annotation of large image datasets is provided. In various embodiments, a plurality of medical images is received. At least one collection is formed containing a subset of the plurality of medical images. One or more image from the at least one collection is provided to each of a plurality of remote users. An annotation template is provided to each of the plurality of remote users. Annotations for the one or more image are received from each of the plurality of remote users. The annotations and the plurality of medical images are stored together.

Abstract: Automatic detection of disease from analysis of echocardiographer findings in echocardiogram videos is provided. In various embodiments, a plurality of medical images containing embedded text are read. The plurality of medical images are clustered into a plurality of clusters. Medical images of a first cluster of the plurality of clusters are ranked based on the frequency of measurement names within the medical images of the first cluster. A candidate tabular template is generated indicative of a layout of measurement name/value pairs within the medical images of the first cluster. According to the candidate tabular template, optical character recognition is applied to one of the plurality of medical images of the first cluster to extract candidate measurements. The candidate tabular template and the candidate measurements are presented to a user.

Abstract: Embodiments of the present invention relate to discriminating between normal and abnormal left ventricles in echocardiography. In some embodiments, a first region of a first image of a heart is located by clustering. The first region depicts a chamber of the heart. The chamber has a chamber shape. A boundary of the first region is determined by contour tracing a retaining the traced contour overlapping the first region. A predetermined shape is compared to the boundary. The predetermined shape had been determined without reference to the first image. A first plurality of parameters is determined that, when applied to the predetermined shape, conforms the predetermined shape to the boundary and minimizes at least one error between the predetermined shape and the boundary. An indication of normality or abnormality is determine from the first plurality of parameters.

Abstract: A pointing method uses eye-gaze as an implicit control channel. A user looks in a natural fashion at a target object as a button on a graphical user interface and then presses a manual selection key. Once the selection key is pressed, the present method uses probability analysis to determine a most probable target object and to highlight it. If the highlighted object is the target object, the user can select it by pressing a key such as the selection key once again. If the highlighted object is not the target object, the user can select another target object using additional keys to navigate to the intended target object.

Abstract: Embodiments of the present invention relate to discriminating between normal and abnormal left ventricles in echocardiography. In one embodiment, a method of and computer program product for discriminating between normal and abnormal left ventricles in echocardiography are provided. A first region of a first image of a heart is located. The first region depicts a chamber of the heart. A boundary of the first region is determined. A predetermined shape is compared to the boundary. A first plurality of parameters is determined that, when applied to the predetermined shape, conforms the predetermined shape to the boundary. The first plurality of parameters is provided to a classifier. An indication of normality or abnormality is received from the classifier.

Abstract: A pointing method uses eye-gaze as an implicit control channel. A user looks in a natural fashion at a target object as a button on a graphical user interface and then presses a manual selection key. Once the selection key is pressed, the present method uses probability analysis to determine a most probable target object and to highlight it. If the highlighted object is the target object, the user can select it by pressing a key such as the selection key once again. If the highlighted object is not the target object, the user can select another target object using additional keys to navigate to the intended target object.

Abstract: An image processing system (100) analyzes novel images in one of three modes. In a first mode, the system learns a model based on vectorized prototype images, and uses the model to characterize the shape of a novel image as a pixel-by-pixel linear combination of the prototype shapes. In a second mode, both shape and texture vectors are used to characterize the novel image as a linear combination of the prototypes. In a third mode, shape information is modeled by a linear combination of prototypes and texture information is modeled by an optical flow, and processing of shape and texture information is interleaved. Novel images are synthesized by analysis of input images using transformed prototypes. Image compression is achieved by storing or transmitting parameter vectors relating the novel or applied images to the prototypes.

Abstract: An image processing system (100) analyzes novel images in one of three modes. In a first mode, the system learns a model based on prototype images, and uses the model to characterize the shape of a novel image as a pixel-by-pixel linear combination of the prototypes. In a second mode, both shape and texture are used to characterize the novel image as a linear combination of the prototypes. In a third mode, shape information is modeled by a linear combination of prototypes and texture information is modeled by an optical flow, and processing of shape and texture information is interleaved. Novel images are synthesized by analysis of input images using transformed prototypes.