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System and method for managing and evaluating network commodities purchasing

A method and system for managing and evaluating commodities purchasing over a network of distributed computing devices. In one embodiment, the method allows a plurality of buyers to generate one request for quote and, response to the request for quote, receive a quote from plurality of vendors. The system of the present invention provides a price normalization routine that allows buyers to evaluate and compare a normalized price for commodity products having different evaluation parameters. In an arrangement comprising a plurality of computers connected to a network said plurality of computers including at least one server, at least one buyer client computer and a plurality of seller client computers, the method for providing commodities exchange services first provides a web-based browsable display describing at least one commodities exchange service. The system then receives at least one request for quote from the buyer. The system then receives at least one quote from different sellers, wherein each quote may have a different price and quantity listed. The system then compares to one or more selected metrics and normalizes the prices received from the different quotes, thus, allowing the buyer to readily compare the prices of a number of commodity items having inherently different values. In one embodiment, the system of the present invention also provides a method for multi-value cross compilation of sales transactions, iterative quote information, and metric data for purposes of evaluation and strategy analysis.
Owner:BUYMETRICS

Maximum likelihood decoding

A method of maximum likelihood decoding for detecting the signals transmitted over a Multiple-Input-Multiple-Output (MIMO) channel of a communication system in which there are N co-channel transmit antennas and M co-channel receive antennas. In a first method an orthotope (22) is generated in input signal space centred on an approximate transmit signal point τ which is an inverse mapping from an actual received signal point (y) in output signal space. Only possible transmit points located within the orthotope are considered as candidate points and are transformed into corresponding candidate receive signal points in output signal space. The Euclidean distance between the candidate receive signal points and the actual signal point is calculated and the closest candidate receive signal is selected as the detected received point. In an alternative method, the orthotope is constructed as the smallest such orthotope which can contain a hyperellipsoid (20) in input signal space, which hyperellipsoid is a transformation from output signal space of a hypersphere (18) centred on the actual received signal point (y). Those transmit signal points which lie within the orthotope (22) but outside of the ellipsoid (20) are discarded and the remaining points within the orthotope are considered as candidate points, in the same way as described above.
Owner:APPLE INC

Reparametrized bull's eye plots

The invention relates to a system for visualizing, in a first bull's eye plot, results of a first quantitative analysis of an object represented in first image data, in particular for cardiac analysis. The first image data comprises a first plurality of data slices, and the system comprises a slice unit for associating a data slice of the first plurality of data slices with a concentric ring of the first bull's eye plot, a radius unit for computing the length of a radius of the concentric ring of the first bull's eye plot, and a value unit for computing at least one value for displaying in the concentric ring of the first bull's eye plot, on the basis of the data slice associated with the concentric ring of the first bull's eye plot, and wherein the length of the radius of the concentric ring of the first bull's eye plot is defined on the basis of the position of the data slice, of the first plurality of data slices, associated with the concentric ring of the first bull's eye plot, with respect to the object. The dependence of the first bull's eye plot concentric ring radius on the position of the data slice associated with said concentric ring of the first bull's eye plot, with respect to the object, defines an objective framework for the first bull's eye plot, based on the geometry of the object. Thus, the results of the first quantitative analysis of the object visualized in the first bull's eye plot can be more easily compared with results of a second quantitative analysis of the same object represented in second image data visualized in a second bull's eye
Owner:KONINKLIJKE PHILIPS ELECTRONICS NV

Model-based grayscale registration of medical images

Numerical image processing of two or more medical images to provide grayscale registration thereof is described, the numerical image processing algorithms being based at least in part on a model of medical image acquisition. The grayscale registered temporal images may then be displayed for visual comparison by a clinician and/or further processed by a computer-aided diagnosis (CAD) system for detection of medical abnormalities therein. A parametric method includes spatially registering two images and performing gray scale registration of the images. A parametric transform model, e.g., analog to analog, digital to digital, analog to digital, or digital to analog model, is selected based on the image acquisition method(s) of the images, i.e., digital or analog/film. Gray scale registration involves generating a joint pixel value histogram from the two images, statistically fitting parameters of the transform model to the joint histogram, generating a lookup table, and using the lookup table to transform and register pixel values of one image to the pixel values of the other image. The models take into account the most relevant image acquisition parameters that influence pixel value differences between images, e.g., tissue compression, incident radiation intensity, exposure time, film and digitizer characteristic curves for analog image, and digital detector response for digital image. The method facilitates temporal comparisons of medical images such as mammograms and/or comparisons of analog with digital images.
Owner:HOLOGIC INC
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