International Business Machines Corporation

Paul T Hurley

Giovanni Cherubini

Andreas Kind

Matthieu M Simeoni

John G Rooney

Patrick Droz

Nezihe Merve Guerel

Maria Gabrani

Tomas Tuma

Krzysztof Kryszczuk

Robin Scheibler

Sanaz Kazemi

Marcel Waldvogel

Marc Stoecklin

Orhan Ocal

Sepand Kashani

Lucien Roquette

Matthieu Martin Jean-Andre Simeoni

Davide Schipani

Matthieu M J Simeoni

Roman Alexander Pletka

Daniel Nikolaus Bauer

Christian Cachin

Christopher J Giblin

Marc Ph Stoecklin

Jan Kunigk

Sean G Rooney

Xenofontas Dimitropoulos

Stefan Apostol

Radu-Christian Ionescu

Rajai Nasser

Joseph Paki

Juri Ranieri

Daniel M Bauer

A method for computing a tissue reflectivity function (TRF) is provided. This method comprises accessing radio-frequency (RF) data and computing a point spread function (PSF), to obtain the TRF. The RF data accessed are data obtained by beamforming time signals from an array of transducers of an ultrasound device. Next, for each pair (r, s) of given pairs of points in the imaging plane, the PSF is computed as a sum of contributions from at least some of the transducers. Each contribution is computed by evaluating a transducer's transfer function, based on two outputs of a respective time-of-flight function. Such outputs are obtained by evaluating the time-of-flight function at a first point r and at a second point s of each pair, respectively. Finally, the RF function can be deconvoluted, based on the computed PSF, so as to obtain the TRF.

Efficient computation of spatially varying ultrasound analytical point spread functions

In a computerized method to reduce noise in phased-array signals from a set of receivers at different locations, time-series are received from the receivers, which time-series form phased-array signals. The time-series are ordered based on the different locations of the receivers and spatially phased series are obtained from the ordered time-series. Each of the spatially phased series obtained includes a series of signal values that are spatially phased. A noise component is identified in each of the spatially phased series obtained and removed from the spatially phased series to obtain denoised series. Related receiver systems and computer program products are also provided.

Reducing noise in phased-array signals from receivers located at different locations

A method of beamforming datasets from a tomographic detection system. The system comprises scintillation detectors that are arranged in D detector pairs, D&#x2265;1, wherein the detectors are adapted to count radiation hits. According to the method in one aspect, a tomographic dataset is received for each detector pair coordinates (&#x3b8;, p) of a detector pair d of the D detector pairs, so as to obtain a plurality of tomographic datasets. Each of said datasets is associated with respective detector pair coordinates (&#x3b8;, p). Then, for each point y of interest, the received datasets are coherently combined by weighting the datasets according to respective beamforming weights(y)=&#x3c9;(&#x3b8;, p; y), based on said respective detector pair coordinates (&#x3b8;, p) and coordinates of said each point y of interest. This way, a signal focusing on said each point y is obtained. Related tomographic detection systems and computer program products may be also presented.

Beamforming for tomographic detection systems

In a method for determining positions {p}of transducers {A}of an apparatus, the transducers are assumed to be configured for receiving wave signals from and/or transmitting wave signals to one or more regions {R}of interest in an n-dimensional space, with n=2 or 3. An n-dimensional spatial filter function {circumflex over (&#x3c9;)}(r) is determined, which matches projections {P}of the one or more regions {R}of interest onto an n&#x2212;1-dimensional sphere centered on the apparatus. Then, a density function &#x192;(p) is obtained, based on a Fourier transform &#x3c9;(p) of the determined spatial filter function {circumflex over (&#x3c9;)}(r). Finally, a position pis determined, within said n-dimensional space, for each of N transducers, based on the obtained density function &#x192;(p) and a prescribed number N of the transducers. The invention is further directed to related devices, apparatuses and systems, as well as computer program products.

Determining positions of transducers for receiving and/or transmitting wave signals

The present invention is directed to methods and apparatuses for beamforming signals or compute beamformed signals. The present approach is to determine a series of beams from or for a set of devices configured for receiving signals from and/or transmitting signals to one or more regions of interest in an n-dimensional space, with n=2 or 3. Each of the devices has a known position pwithin said n-dimensional space. Signals are to be respectively transmitted or received non-uniformly in this space, i.e., according to the particular regions of interest. During a first phase, operations are performed in order to successively obtain a spatial filter function {circumflex over (&#x3c9;)}(r), a beamforming function &#x3c9;(p), and beamforming weights &#x3c9;(p). The spatial filter function {circumflex over (&#x3c9;)}(r) matches projections of the regions of interest onto an n&#x2212;1-dimensional sphere centered on said set of devices. The function {circumflex over (&#x3c9;)}(r), however, extends over the n-dimensional space and does not restrict to the n&#x2212;1-dimensional sphere. During a second phase, delays and gains are suitably introduced in the signals, by weighting time-series according to beamforming weights &#x3c9;(p) obtained during the first phase.

Methods and apparatuses for versatile beamforming

A system and method for restricting the number of layout patterns by pattern identification, matching and classification, includes decomposing the pattern windows into a low frequency component and a high frequency component using a wavelet analysis for an integrated circuit layout having a plurality of pattern windows. Using the low frequency component as an approximation, a plurality of moments is computed for each pattern window. The pattern windows are classified using a distance computation for respective moments of the pattern windows by comparing the distance computation to an error value to determine similarities between the pattern windows.

IC layout pattern matching and classification system and method

The present invention is notably directed to a computer-implemented method for image reconstruction. The method comprises: accessing elements that respectively correspond to measurement values, which can be respectively mapped to measurement nodes; and performing message passing estimator operations to obtain estimates of random variables associated with variable nodes, according to a message passing method in a bipartite factor graph. In this message passing method: the measurement values are, each, expressed as a term that comprises linear combinations of the random variables; each message exchanged between any of the measurement nodes and any of the variable nodes is parameterized by parameters of a distribution of the random variables; and performing the message passing estimator operations further comprises randomly mapping measurement values to the measurement nodes, at one or more iterations of the message passing method. Finally, image data are obtained from the obtained estimates of the random variables, which image data are adapted to reconstruct an image. The present invention is further directed to related systems and methods using the above image reconstruction method.

Image reconstruction using approximate message passing methods

The present invention is notably directed to computer-implemented methods and systems for recovering an image. Present methods comprise: accessing signal data representing signals; identifying subsets of points arranged so as to span a region of interest as current subsets of points; reconstructing an image based on current subsets of points, by combining signal data associated to the current subsets of points; detecting one or more signal features in a last image reconstructed; for each of the detected one or more signal features, modifying one or more subsets of the current subsets, so as to increase, for each of the modified one or more subsets, a relative number of points at a location of said each of the detected one or more signal features. The relative number of points of a given subset at a given location may be defined as the number of points of said given subset at the given location divided by the total number of points of said given subset, whereby new current subsets of points are obtained; and repeating the above steps of reconstructing, detecting and modifying, as necessary to obtain a reconstructed image that satisfies a given condition.

Iterative image subset processing for image reconstruction

Embodiments include methods for calibrating sensors of one or more sensor arrays. Aspects include accessing one or more beamforming matrices respectively associated to the one or more sensor arrays. Source intensity estimates are obtained for a set of points in a region of interest, based on measurement values as obtained after beamforming signals from the one or more sensor arrays based on the one or more beamforming matrices, assuming fixed amplitude and phase of gains of sensors of the one or more sensor arrays. Estimates of amplitude and phase of the sensor gains are obtained based on: measurement values as obtained before beamforming; and the previously obtained source intensity estimates. The obtained estimates of amplitude and phase can be used for calibrating sensors.

Blind calibration of sensors of sensor arrays

Technology for managing beamformed signals. A method includes: receiving beamformed signals from one or more arrays of receiving elements, which one or more arrays of receiving elements send beamformed signals at given transmission rates; recovering information from the received beamformed signals; measuring a quality of the recovered information, using a metric that estimates a distance between the recovered information and reference information; and, based on the measured quality, instructing the one or more arrays of receiving elements to change the transmission rates at which they send beamformed signals.

Managing beamformed signals to optimize transmission rates of sensor arrays

Apparatus and method for scheduling event streams. The apparatus includes (i) an interface for receiving event streams which are placed in queues and (ii) a scheduler which selects at least one event stream for dispatch depending on sketched content information data of the received event streams. The scheduler includes a sketching engine for sketching the received event streams to determine content information data and a selection engine for selecting at least one received event stream for dispatch depending on the determined content information data of the received event streams. The method includes the steps of (i) determining content information data about the content of event streams and (ii) selecting at least one event stream from the event streams for dispatch depending on the content information data. A computer program, when run by a computer, causes the computer to perform the steps of the above method.

Scheduling event streams depending on content information data

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Zurich, Switzerland

Paul T Hurley