Ge Medical Systems Global Technology Company, LLC

Sharon Xiaorong Wang

Stephen Wayne Metz

Thomas L Toth

Piero U Simoni

Jiang Hsieh

John Fusco

Jianying Li

Brian Grekowicz

Min Xie

Roy-Arnulf Helge Nilsen

A method for computing a natural logarithm function includes partitioning a mantissa region between 1 and 2 into N equally spaced sub-regions; precomputing a reference point aof each of the N equally spaced sub-regions, where i=0, . . . ,N&#x2212;1; selecting N sufficiently large so that, within each sub-region, a first degree polynomial in m computes log(m) to within a preselected degree of accuracy for any m within the sub-region, where m is a mantissa of a binary floating point representation of a variable x; and computing a value of log(x) for a binary floating point representation of x stored in a memory of a computing device utilizing the first degree polynomial in m.

Method and apparatus for fast natural log(X) calculation

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

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

One aspect of the present invention is a method for reconstructing computed tomographic (CT) images. The method includes generating a plurality of projection data, calculating a plurality of base weights using the projection data for each series of images to be reconstructed, storing the base weights in an external memory, and applying a z-smoothing module to the base weights to determine a plurality of final weights. The view weighting process then includes applying the final weights to the projection data for each image.

Scan data correction view weighting of computed tomographic images

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

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 rows in a CT detector, weighting the data arrays using a unique weighting function that including different weighting functions for a first detector row, a last detector row and the middle detector rows between the first and last detector rows thereby generating helical weighted arrays for each row, applying a half scan weight to each helical weighted array and using the half scan weighted arrays to generate a slice image.

Helical segment image reconstruction

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.

Methods and apparatus for high pitch helical computed tomography image reconstruction

Helical rowwise view weighting of computed tomographic images

There is therefore provided, in one embodiment of the present invention, a method for reconstructing a volume image of an object. The method includes steps of scanning an object with a multislice computed tomographic (CT) imaging system having a multislice detector array to acquire projection data of a volume of the object; filtering the acquired projection data; and backprojecting the filtered projection data to reconstruct voxels of the volume image. The multislice detector array has a plurality of rows and columns of detector elements and the backprojecting includes interpolating the filtered projection data across both rows and columns of the multislice detector array.

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Brookfield, WI, United States of America

Sharon Xiaorong Wang