Ge Medical Systems Global Technology Company, LLC

General Electric Company

Piero U Simoni

Thomas L Toth

Stephen Wayne Metz

Sharon Xiaorong Wang

Xiaoye Wu

Neil Barry Bromberg

Jiang Hsieh

Jianying Li

Alexander Kolker

An apparatus and process for determining and displaying an artifact index (AI) to a system operator are provided. The AI is determined by acquiring and processing imaging data of a phantom. The AI is then displayed to the operator on a console so that the operator may, if necessary, reset the scanning parameters or select a new scanning protocol that will result in a reconstructed image of a subject having reduced artifact presence. By providing a likelihood of artifact presence to the system operator, the present invention eliminates the need for the operator to recall those scanning profiles that are susceptible to high artifact presence.

Method and apparatus of determining and displaying an artifact index

A method for determining a correction for beam hardening in CT images includes obtaining air scans at a plurality of kVp's, determining detection efficiencies for detector elements of the CT imaging apparatus, and estimating projection values through a combination of at least two different materials of different thicknesses. The method further includes determining a transfer function that translates the estimated projection values into ideal projection values for at least two of the different materials and storing the transfer function as the beam hardening correction for images of the CT imaging apparatus.

Method and apparatus for correcting for beam hardening in CT images

A method for calibrating a computed tomographic imaging apparatus having a gantry, a radiation source operable at a plurality of kVp's, and a detector array having a plurality of detector elements includes using a system detection function to estimate signals of each detector element that would have been detected through air and through a given thickness of water to determine estimated datasets. The estimated datasets are used to determine data pair sets each comprising a normalized water projection value and an ideal projection value for each detector element. The method further includes determining and storing a representation of a mapping function of the normalized water projections values to the ideal projection values in a memory of the computed tomographic imaging apparatus as a spectral calibration of the computed tomographic imaging apparatus.

Methods for spectrally calibrating CT imaging apparatus detectors

A method for reconstructing an image of an object utilizing a computed tomographic (CT) imaging system having a radiation source configured to project a beam of radiation through an object and towards a multislice detector array configured to sense attenuation of the radiation passing through the object; the method includes helically scanning an object to acquire a plurality of slices of projection data, generating a separate projection dataset for each of N separate detector rows wherein the separate projection datasets include detector row projection data and detector row conjugate projection data, combining the detector row projection data and the detector row conjugate projection data, and helically weighting the combined projection data using a combined helical weighting and conjugate data weighting algorithm such that a greater weight is applied to combined center row projection data than to at least one outermost detector row projection data.

Methods and apparatus for reconstructing an image of an object

An apparatus and process for determining and displaying a helical artifact index to a system operator are provided. The HAI is determined by acquiring and processing imaging data of a phantom. The HAI is then displayed to the operator on a console so that the operator may, if necessary, reset the scanning parameters or select a new scanning protocol that will result in a reconstructed image of a subject having reduced artifact presence. By providing a likelihood of artifact presence to the system operator, the present invention eliminates the need for the operator to recall those scanning profiles that are susceptible to high artifact presence.

Method of determining and displaying a helical artifact index

A method and apparatus for quickly rendering thick CT slice images wherein the data corresponding to an optimal number of slice images to be combined to generate a thick image and the data set required to generate the thick image are determined as a function of an optimal Z-smoothing factor and wherein Z-smoothing is implemented in software that performs quickly and is useable with any helical weighting algorithm and Z-smoothing function.

High Speed Z-smoothing method and apparatus for CT imaging system

Method and apparatus of determining and displaying a helical artifact index

A method and apparatus for performing image reconstruction using data obtained by an N beam helical scan, the method including generating projection data arrays for each of the N row in a CT detector, weighting the data arrays using a unique weighting function that is applicable to detectors having many different numbers of rows N to generate helical weighted arrays for each row, weighting the helical weighted arrays by applying a conjugate weighting function to generate conjugate arrays for each detector row and then combining the conjugate weighted arrays, filtering and back-projecting to generate a slice image.

Row-wise full helical view weighting method and apparatus for CT scanners

There is therefore provided, in one aspect, a method for imaging an object utilizing a computed tomographic (CT) imaging system having a rotating gantry, a multislice detector array on the rotating gantry and using at least n>1 rows of detector channels, and a radiation source on the rotating gantry configured to project a beam of radiation towards the multislice detector array through an object to be imaged. The method includes helically scanning the object with the CT imaging system at a pitch p>n to acquire projection data from the n rows of detector channels; applying a combined helical weight and conjugate weight to at least a portion of the acquired projection data to produce virtual projection data compensating for incomplete helical row data of the acquired projection data; and reconstructing an image of the object utilizing the acquired projection data and the virtual projection data.

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New Berlin, WI, United States of America

Piero U Simoni