International Business Machines Corporation

Mayo Foundation for Medical Education and Research

Nuance Communications, Inc.

Nelson Ramirez

Jeffrey S McAllister

Timothy John Mullins

Armando Manduca

David S Lake

David Glenn Carlson

Travis Michael Drucker

Daniel J Blezek

Bradley J Erickson

Peter John Schommer

David Roy Limpert

Mark A Bransford

A method, apparatus, and program product stream data between a host element and a target element in a parallel computing system. The method comprises partitioning data used to perform a task into a plurality of data streams based at least in part upon data associated with the task and partitioning a data stream into a plurality of data stream views based at least in part on a memory size associated with a target element configured to process the data stream. The method further comprises sequentially communicating at least a portion of the data stream views to the target element via a data streaming infrastructure implemented on at least a host element and the target element, wherein the portion of the data streaming infrastructure on the host element transfers the portion of the data stream views to the portion of the data streaming infrastructure on the target element.

Data streaming infrastructure for remote execution in a constrained environment

A system and/or method automatically identifies one or more vascular regions in a medical image or set of medical images. For example, the system/method may automatically identify vascular structures as belonging to the left carotid, right carotid, and/or basilar vascular regions in the head. The system/method takes as input the medical image(s) and automatically identifies one or more vascular regions. The system/method may also automatically generate MIP renderings of the identified region or regions.

Automated vascular region separation in medical imaging

Systems, methods and articles of manufacture are disclosed for compensating for motion of a subject during an MRI scan of the subject. k-space data may be received from the MRI scan of the subject. Motion information may be received for the subject. Based on the received motion information, a translational motion of the subject may be determined between a first point in time and a second point in time. A search space for motion correction may be reduced using the determined change and an error margin of the capturing technique. A motion-compensated, graphical image of the subject may be generated using the reduced search space.

Physical motion information capturing of a subject during magnetic resonce imaging automatically motion corrected by the magnetic resonance system

Systems, methods and articles of manufacture are disclosed for transposing array data on a SIMD multi-core processor architecture. A matrix in a SIMD format may be received. The matrix may comprise a SIMD conversion of a matrix M in a conventional data format. A mapping may be defined from each element of the matrix to an element of a SIMD conversion of a transpose of matrix M. A SIMD-transposed matrix T may be generated based on matrix M and the defined mapping. A row-wise algorithm may be applied to T, without modification, to operate on columns of matrix M.

Transposing array data on SIMD multi-core processor architectures

Systems, methods and articles of manufacture are disclosed for capturing motion information in a magnetic resonance imaging (MRI) environment. A light sink in the MRI environment may detect light emitted from a plurality of light sources. Each of the plurality of light sources may emit light of a different frequency. Further, each of the plurality of light sources may be located at a different spatial position in the MRI environment. The detected light may be analyzed. A change in spatial position of the light sink may be computed based on the analysis.

Real time motion information capture in an MRI environment

Techniques are disclosed for converting data into a format tailored for efficient multidimensional fast Fourier transforms (FFTS) on single instruction, multiple data (SIMD) multi-core processor architectures. The technique includes converting data from a multidimensional array stored in a conventional row-major order into SIMD format. Converted data in SIMD format consists of a sequence of blocks, where each block interleaves s rows such that SIMD vector processors may operate on s rows simultaneously. As a result, the converted data in SIMD format enables smaller-sized 1D FFTs to be optimized in SIMD multi-core processor architectures.

Processing array data on SIMD multi-core processor architectures

Techniques are disclosed for generating fast vector masking SIMD code corresponding to source code having a conditional statement, where the SIMD code replaces the conditional statements with vector SIMD operations. One technique includes performing conditional masking using vector operations, bit masking operations, and bitwise logical operations. The need for conditional statements in SIMD code is thereby removed, allowing SIMD hardware to avoid having to use branch prediction. This reduces the number of pipeline stalls and results in increased utilization of the SIMD computational units.

Fast vector masking algorithm for conditional data selection in SIMD architectures

Techniques are disclosed for automating the generation of parallel SIMD native source code in three major functional areas of data transmission, synchronization, and SIMD operations. An annotation standard is defined that is independent from native compilers and, coupled with a source-to-source compiler that provides high-level abstractions of data transmission, synchronization, and SIMD operations, relieves the need for programmers to work in a hardware-specific manner, while addressing issues of productivity and portability in a parallel SIMD computing environment.

Generating parallel SIMD code for an arbitrary target architecture

Systems, methods and articles of manufacture are disclosed for compensating for motion of a subject during an MRI scan of the subject. k-space data may be received from the MRI scan of the subject. A first graphical image may be generated from a first set of data elements from the k-space data. Similarly, a second graphical image may be generated from a second set of data elements from the k-space data. An offset in pixels may be determined by which to translate the second graphical image from the first graphical image to compensate for the motion. The k-space data may be modified at a sub-pixel offset relative to the determined offset. A motion-compensated graphical image of the subject may be generated from the modified k-space data. Doing so reduces the search space evaluated to sharpen images generated from the k-space data.

Correcting subject motion in multiple resolutions in magnetic resonance imaging

A technique is disclosed for distributed runtime diagnostics in hierarchical parallel environments. In one embodiment, a user is allowed to configure, during runtime, a processing element on which to perform diagnostics, an algorithm for the processing element to execute, a data set for the algorithm to execute against, a diagnostic function for the processing element to execute, a condition for executing the diagnostic function, and visualization parameters for memory local to the processing element. As a result, runtime diagnostics can be performed with sufficient degree of control and customization to aid debugging in a hierarchical parallel environment.

Distributed runtime diagnostics in hierarchical parallel environments

Controlling a computer user interface with sound including defining ranges of audio frequencies; associating each range with a user interface command; receiving as input from a user a sound representing an instruction to execute a user interface command, the sound characterized by a spectrum of frequencies and energies; identifying the user interface command to be executed in dependence upon the spectrum of frequencies and energies, the defined ranges of audio frequencies, and the user interface commands associated with the ranges; and executing the identified command.

Growing community of inventors

Rochester, MN, United States of America

Nelson Ramirez