General Electric Company

Mayo Foundation for Medical Education and Research

International Business Machines Corporation

Daniel J Blezek

Bradley J Erickson

Christopher Judson Hardy

William Thomas Dixon

Paritosh Jayant Dhawale

Rakesh Mullick

Thomas K F Foo

Ricardo Scott Avila

Robert August Kaucic

Shekhar Dwivedi

Luca Marinelli

William Macomber Leue

David F Kallmes

Nelson Ramirez

Vivek Prabhakar Vaidya

Timothy Patrick Kelliher

Peter John Schommer

David Roy Limpert

Brian J Bartholmai

Umesha Perdoor Srinivas Adiga

Xiaojiang Yang

Zachary Kelm

A computer-aided system identifies aneurysm suspects in 3D image datasets. The system takes the raw image dataset as input and assigns one or more points of interest (POIs) in the image data. The system determines one or more features for each POI and identifies one or more aneurysm suspects from among the assigned POIs based on the determined features.

Computer-aided detection (CAD) of intracranial aneurysms

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

A computer-implemented method for reducing noise in an image includes receiving a first image in a computer system. The first image depicts an interior of an item and is generated using a technique that provides imaging at selected depths in the item. The first image represents a first interior section having a first thickness. The method includes determining a modification for the first image using a second image of the interior. The second image represents a second interior section encompassing the first interior section and has a second thickness greater than the first thickness. The method includes storing the modification in association with the first image.

Reducing noise in an image

An apparatus, system and method to determine a coordinate system of a heart includes an imager and a computer. The computer is programmed to acquire a first set of initialization imaging data from an anatomical region of a free-breathing subject. A portion of the first set of initialization imaging data includes organ data, which includes cardiac data. The computer is further programmed to determine a location of a central region of a left ventricle of a heart, where the location is based on the organ data and a priori information. The computer is also programmed to determine a short axis of the left ventricle based on the determined location, acquire a first set of post-initialization imaging data from the free-breathing subject from an imaging plane orientation based on the determination of the short axis, and reconstruct at least one image from the first set of post-initialization imaging data.

System and method for determining a cardiac axis

A method for reconstructing an image in a magnetic resonance imaging system is provided. The method includes steps of acquiring magnetic resonance signals from a plurality of receiver coils placed about a subject, each receiver coil having a coil sensitivity, iteratively polling each acquired magnetic resonance signal for determining one or more significant wavelet components of each acquired magnetic resonance signal by utilizing a coil sensitivity function of each receiver coil for each acquired magnetic resonance signal, iteratively determining one or more coefficients based on the one or more significant wavelet components to generate a plurality of coefficients for each acquired magnetic resonance signal, reconstructing an image utilizing a corresponding plurality of coefficients corresponding to each acquired magnetic resonance signal, and generating a composite image by combining the reconstructed images.

Method and system for reconstructing images

Systems and methods for identifying the relative contribution of fat and water signals in a magnetic resonance ('MR') image including an algorithm operable for selecting an image signal model, selecting a scan parameter, forming a bias field estimate, applying a bias correction to a phase image, estimating the signal fraction of fat and water at each of a plurality of voxels, and forming a fat-suppressed image, a water-suppressed image, or a combination of a fat-based image and a water-based image. The ('MRI') fat suppression systems and methods requiring only a single image acquisition including an algorithm operable for selecting a relative phase of approximately &#x3b8;=&#x3c0;/2 or another suitable relative phase, employing an expectation maximization algorithm to classify the phase of the complex image, and projecting complex vectors into fat and water components to obtain fat and water images.

Fat/water separation and fat minimization magnetic resonance imaging systems and methods

A system and a method for detecting an object, such as an explosive device or material, located within a closed article, such as a piece of luggage or a parcel. The system includes an acquisition subsystem for acquiring information pertaining to a specific object, a reconstruction subsystem for reconstructing acquired information pertaining to the specific object into image data, and a computer-aided detection subsystem adapted for identifying the specific object through the use of differential operators. The method includes obtaining image data of the one object, computing a differential operator for each voxel of the image data, computing eigenvalues and eigenvectors for each of the voxels, and computing a scalar function of the eigenvalues to ascertain whether each of the voxels represents a portion of the one object.

System and method for detecting objects with differential operators

Magnetic resonance imaging ('MRI') systems and methods for acquiring multi-slice gradient echo images having a substantially constant T-weighting including selecting a first scan having a desired contrast associated with T-weighting and, given a first repetition time, TR, and a first flip angle, flip, associated with the first scan, selecting an effective repetition time, TReff, that provides the desired contrast. The MRI systems and methods also including holding the effective repetition time, TReff, substantially constant in relation to a second scan. The MRI systems and methods further including, given a second repetition time, TR, determining a second flip angle, flip, and, given the second flip angle, flip, determining the second repetition time, TR. The MRI systems and methods still further including performing the second scan using the second repetition time, TR, and the second flip angle, flip, and maximizing a signal-to-noise ratio, S/N, of the second scan.

Magnetic resonance imaging systems and methods for acquiring multi-slice gradient echo images

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Mantorville, MN, United States of America

Daniel J Blezek