General Electric Company

Mary Sue Kulpins

Jiang Hsieh

Xiaoye Wu

Naveen Stephan Chandra

Roy A Nilsen

Jiahua Fan

Evgeny Drapkin

Thomas L Toth

Daniel David Harrison

Jed Douglas Pack

Baojun Li

Dan Xu

Xiangyang Tang

Paavana Sainath

Hui David He

Fang Frank Dong

Dominic Joseph Crotty

Thomas John Myers

Grant Morey Stevens

Neil Barry Bromberg

Roy-Arnulf Helge Nilsen

Franco Rupcich

Peter S Crandall

Zhanyu Ge

Andrew C Johnson

Methods and systems are provided for automatic exposure control in computed tomography imaging systems. In one embodiment, a method comprises in response to an object-specific dose metric input by a user via a user interface operably coupled to a scanner, predicting an image quality of a diagnostic scan, calculating an output level of a source of the scanner for the image quality, and performing the diagnostic scan at the output level when the image quality is higher than a threshold. In this way, patient-specific image quality settings may be determined.

Methods and systems for computed tomography

A method is provided that includes acquiring a first set of image data from X-rays produced at a first energy level and a second set of image data from X-rays produced at a second energy level. The method includes generating a first noise mask for a first basis material and a second noise mask for a second basis material and removing pixels corresponding to cross contaminating structural information from the first noise mask and the second noise mask. The method includes processing a first materially decomposed image generated from the first set of image data and the second set of digital data using the second noise mask after removal of the cross contaminating structural information and processing a second MD image generated from the first set of image data and the second set of digital data using the first noise mask after removal of the cross contaminating structural information.

Noise reduction method for dual-energy imaging

A CT system includes a generator configured to energize an x-ray source to a first kilovoltage (kVp) and to a second kVp, and a computer that is programmed to acquire a first view dataset with the x-ray source energized to the first kVp and a second view dataset with the x-ray source energized to the second kVp, generate a base correction image using the first view dataset and the second view dataset, and reconstruct a pair of base material images from the first view dataset and from the second view dataset. The computer is also programmed to estimate artifact correlation in the pair of base material images using the base correction image, generate a pair of final base material images and a final monochromatic image, and correct one of the pair of final base material images and the final monochromatic image at a keV value using the estimated artifact correlation.

System and method of image artifact reduction in fast kVp switching CT

An imaging system includes an x-ray source that emits a beam of x-rays toward an object, a detector that receives high frequency electromagnetic energy attenuated by the object, a data acquisition system (DAS) operably connected to the detector, and a computer operably connected to the DAS. The computer is programmed to compute detector coefficients based on a static low kVp measurement and a static high kVp measurement, capture incident spectra at high and low kVp during fast kVp switching, compute effective X-ray incident spectra at high and low kVp during fast kVp switching using the captured incident spectra, scan a water phantom and normalize the computed detector coefficients to water, adjust the computed effective X-ray incident spectra based on the normalized detector coefficients, compute basis material decomposition functions using the adjusted X-ray incident spectra, and generate one or more basis material density images using the computed basis material decomposition functions.

System and method of spectral calibration and basis material decomposition for X-ray CT systems

A method for performing BIS correction includes scanning an object with a computed tomography (CT) system to obtain data, reconstructing an image using the obtained data, and using the image to perform BIS correction.

Methods and apparatus for BIS correction

A method and apparatus for processing raw image data to create processed images. Raw image data is acquired. The raw image data is decomposed by a data decomposer into N subsets of raw image data. The number N is based on a number of available image generation processors. The N subsets of raw image data are processed by at least one image generation processor to create processed image data. If more than one image generation processor is available, the image generation processors perform image processing on the raw image data in parallel with respect to each other.

Method and apparatus for image reconstruction using data decomposition for all or portions of the processing flow

Methods and apparatus for detecting cell to cell variation to ensure that the maximum allowable channel to channel variation is not exceeded are described. In one embodiment, an algorithm is periodically executed to measure the relative gains in the channels. The gains are measured, for example, by recording the signal from an air scan and normalizing to a common reference. Part of the normalization process includes accounting for the non uniformity of the x-ray beam, for example, the heel effect. It is assumed that the x-ray flux profile in z is slowly changing in the x-direction and is obtained by low pass filtering in x. The normalized values are then compared to a predetermined specification. If any particular cell is not within the specification parameters, then the module in which such cell resides may be replaced. In addition to measuring gain variation and comparing it to a specification, a trending analysis also may be performed. The trending algorithm predicts the time at which the detector will fail the specification so that replacement of the detector may take place before failure occurs.

Methods and apparatus for monitoring detector image quality

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Brookfield, WI, United States of America

Mary Sue Kulpins