Abstract: A method, system, computer program product, and apparatus for reducing wasted bandwidth due to supercasting multicast cells through a router switch fabric is presented. A multicast destination address is compared to each destination address in a label-to-destination address table (LTDT) to determine the wasted bandwidth due to incorporating any additional switch fabric ports designated by the new destination address with beyond the switch fabric ports designated for each LTDT entry. Also considered is the amount of traffic experienced by each LTDT entry and that expected for the new destination address.

Abstract: A method, computer program product, system and apparatus are presented for reducing wasted bandwidth due to supercasting multicast cells through a router switch fabric. In one embodiment of the present invention, signatures of a switch fabric destination address are generated and compared. A signature is an information-rich representation of the fabric destination address that is generated using the fabric destination address. Therefore, supercasting can be minimized by combining fabric destination addresses with like signatures. Aspects of the present invention include generating the signatures using random permutation maps of the set of switch fabric ports or determining intersections of a fabric destination address with a selection of subsets of the switch fabric ports.

Abstract: A user adjusts the performance for assisted diagnosis. The sensitivity, specificity or both are adjusted as desired by the physician or end-user. By adjusting the trade-offs, a decision support system may be optimized by each user or for each case, possibly avoiding a one-fits-all approach or requiring purchase of different CAD products.

Abstract: A system and method for diagnosis and treatment decisions based on information maximization is disclosed. Utilizing patient information as well as clinical records from other patients can reduce the uncertainty in both diagnosis and treatment options. The information maximization may consider additional data such as risk, cost, and comfort in making a proper medical decision.

Abstract: Missing data is addressed in a medical decision support system. The classifier applied to the patient record with missing data is obtained as a function of the available data. For example, one of a plurality of different classifiers is selected based on the features available in the patient record to be classified. The different classifiers are developed using different feature sets. The classifier developed using a feature set closest to or a sub-set of the features available in the patient record is selected for classifying the patient record. As another example, features in a training set corresponding to features available in the patient record are used to build a classifier. The classifier is applied to the patient record by inputting the available features of the patient record.

Abstract: A data replication facility for distributed computing environments. A computer network having a plurality of network nodes utilizes a distributed directory provider service (DPS) having an established master node. The DPS supports a file replication service (FRS). The FRS establishes one of the nodes as originator node which receives new or updated files from one or more user/GUIs and/or from one or more software providers such as a security provider. The originator node in cooperation with the master node establish a backup copy of the new or updated file in the master node. Thereafter, the originator node publishes a File Version Variable (FVV) representation of the new or updated file to other network nodes (slave nodes) which obtain such file from the originator or, if need be, from the backup master node.

Abstract: Automated analysis of heart function is provided with ultrasound images. A clip of ultrasound images of the heart is used to detect two or three dimensional motion, such as determining a two-dimensional motion vector by tracking wall segments with B-mode data. The amplitude of motion during the e-wave and/or a-wave phase of diastole is extracted for diagnosis assistance.

Abstract: Motion is automatically characterized from ultrasound information. Ultrasound information associated with particular time periods relative to a cycle, such as the cardiac cycle, are extracted, such as identifying and extracting ultrasound information associated with systole. By tracking an area of the heart, such as an area within the endocardial contour, the heart cycle time periods are identified. Spatial parameter values are determined as a function of time from the extracted ultrasound information. For example, the timing of motion, the eigen motion, the curvature, the local ejection-fraction ratio and/or the bending energy of parts of the cardiac tissue are determined. The spatial parameter values characterize the motion.

Abstract: Ultrasound signal information is detected from a sequence of images. A robust automated delineation of the border of the fan or ultrasound signal information in echocardiographic or other ultrasound image sequence is provided. The processor implemented delineation uses a single image or a sequence of images to better identify ultrasound signal data. Variation through a sequence generally identifies the signal area. Projecting the filtered variation information to two likely directions identifies approximate edge locations along the sides of the border. Robust regression fits lines to the edges to find accurate border locations. The bottom of the border is identified with a histogram of the variation information as a function of radius from an intersection of the fit lines.

Abstract: A cardiac view of a medical ultrasound image is automatically identified. By grouping different views into sub-categories, a hierarchal classifier identifies the views. For example, apical views are distinguished from parasternal views. Specific types of apical or parasternal views are identified based on distinguishing between images of the geneses. Different features are used for classifying, such as gradients, functions of the gradients, statistics of an average frame of data from a clip or sequence of frames, or a number of edges along a given direction. The number of features used may be compressed, such as by classifying a plurality of features into a new feature. For example, alpha weights in a model of features and classes are determined and used as features for classification.

Abstract: By inputting genetic and imaging information into a trained classification system, a second opinion diagnosis, a prognosis, clinical trial qualification or similar case information are output to assist a user. Consistent analysis may be provided using image based measurements in combination with pharmacogenomics studies. Fusing imaging, genetics and other information, such as clinical data, may more likely reduce the number of uncertainties in medical analysis, possibly improving patient safety, identifying new capabilities and supporting research.

Abstract: Systems and methods are provided for processing a medical image to automatically identify the anatomy and view (or pose) from the medical image and automatically assess the diagnostic quality of the medical image. In one aspect a method for automated decision support for medical imaging includes obtaining image data, extracting feature data from the image data, and automatically performing anatomy identification, view identification and/or determining a diagnostic quality of the image data, using the extracted feature data.

Abstract: Business methods and systems that are provided use knowledge-based expert systems for mining (extracting) highly structured clinical information from various structured and unstructured sources of healthcare provider data. In one business method for on-line healthcare management and decision support, a service provider maintaining a collection of structured clinical data, the structured clinical data comprising information automatically mined from various structured and unstructured sources of healthcare provider data from one or more different healthcare providers. The service provider provides a customer on-line access to structured clinical data in the collection, or providing an on-line service to the customer using structured clinical data in the collection, based on a service agreement between the customer and the service provider.

Abstract: Hierarchal modeling is used to distinguish one state or class from three or more classes. In a first stage, a normal or other class is distinguished from a diseased or other groups of classes. If the results of the first stage classification indicate diseased or data within the groups of different classes, a subsequent stage of classification is performed. In a subsequent stage of classification, the data is classified to distinguish one or more other classes from the remaining classes. Using two or more stages, medical information is classified by eliminating one or more possible classes in each stage to finally identify a particular class most appropriate or probable for the data.

Abstract: A system and method for local deformable motion analysis and for accurately tracking motion of an object isolating local motion of an object from global motion of an object is disclosed. The object is viewed in an image sequence and image regions are sampled to identify object image regions and background image regions. The motion of at least one of the identified background image regions is estimated to identify those background image regions affected by global motion. Motion from multiple background image regions are combined to measure the global motion in that image frame. The measured global motion in the object image regions are compensated to measure local motion of the object and the local motion of the object is tracked. A system and method for accurately measuring the local deformable motion of an object as the relative motion between two control point sets is disclosed. The point sets are defined as the inner contour and the outer contour of an object.

Abstract: Systems and methods are provided for automated assessment of regional myocardial function using wall motion analysis methods that analyze various features/parameters of patient information (image data and non-image data) obtained from medical records of a patient. For example, a method for providing automatic diagnostic support for cardiac imaging generally comprises obtaining image data of a heart of a patient, obtaining features from the image data of the heart, which are related to motion of the myocardium of the heart, and automatically assessing regional myocardial function of one or more regions of a myocardial wall using the obtained features.

Abstract: CAD (computer-aided diagnosis) systems and applications for breast imaging are provided, which implement methods to automatically extract and analyze features from a collection of patient information (including image data and/or non-image data) of a subject patient, to provide decision support for various aspects of physician workflow including, for example, automated diagnosis of breast cancer other automated decision support functions that enable decision support for, e.g., screening and staging for breast cancer. The CAD systems implement machine-learning techniques that use a set of training data obtained (learned) from a database of labeled patient cases in one or more relevant clinical domains and/or expert interpretations of such data to enable the CAD systems to “learn” to analyze patient data and make proper diagnostic assessments and decisions for assisting physician workflow.

Abstract: CAD (computer-aided diagnosis) systems and applications for cardiac imaging are provided, which implement methods to automatically extract and analyze features from a collection of patient information (including image data and/or non-image data) of a subject patient, to provide decision support for various aspects of physician workflow including, for example, automated assessment of regional myocardial function through wall motion analysis, automated diagnosis of heart diseases and conditions such as cardiomyopathy, coronary artery disease and other heart-related medical conditions, and other automated decision support functions. The CAD systems implement machine-learning techniques that use a set of training data obtained (learned) from a database of labeled patient cases in one or more relevant clinical domains and/or expert interpretations of such data to enable the CAD systems to “learn” to analyze patient data and make proper diagnostic assessments and decisions for assisting physician workflow.

Abstract: A system and method for tracking a global shape of an object in motion is disclosed. One or more control points along an initial contour of the global shape are defined. Each of the one or more control points is tracked as the object is in motion. Uncertainty of a location of a control point in motion is represented using a number of techniques. The uncertainty to constrain the global shape is exploited using a prior shape model. In an alternative embodiment, multiple appearance models are built for each control point and the motion vectors produced by each model are combined in order to track the shape of the object. The movement of the shape of the object can be visually tracked using a display and color vectors.

Abstract: A medical ultrasound imaging pulse transmission method transmits at least three pulses, including at least two pulses of different amplitude and at least two pulses of differing phase. The larger-amplitude pulse is transmitted with a larger aperture and the smaller-amplitude pulses are transmitted with respective smaller subapertures. The subapertures are arranged such that the sum of the subapertures used for the smaller-amplitude pulses is equal to the aperture used for the larger-amplitude pulse. In this way, pulses of differing amplitudes are obtained without varying the power level of individual transducer elements, and precise control over pulse amplitude is provided.