General Electric Company

University of Notre Dame Du Lac

Purdue Research Foundation

Guangzhi Cao

Jiang Hsieh

Jiahua Fan

Brian Edward Nett

Jean-Baptiste Thibault

Jed Douglas Pack

Ken David Sauer

Zhou Yu

Saad Ahmed Sirohey

Bruno Kristiaan Bernard De Man

Charles Addison Bouman

Lin Fu

Bruno De Man

Kai Zeng

Debashish Pal

Roy A Nilsen

Hewei Gao

Grant Morey Stevens

David Joseph Pitterle

Evgeny Drapkin

Suresh Narayanan Narayanan

Edgar Chino

Tonghe Wang

Yunzhe Zhao

Various methods and systems for dual energy spectral computed tomography imaging are provided. In one embodiment, a method for dual energy imaging comprises generating an image from a higher energy dataset and an updated lower energy dataset, wherein the updated lower energy dataset comprises a combination of a lower energy dataset and a pseudo projection dataset generated from the higher energy dataset. In this way, a weak low energy signal may be recovered, thereby enabling image reconstruction in spite of photon starvation and sparse views.

Methods and systems for spectral CT imaging

Various methods and systems are provided for estimating and compensating for table deflection in reconstructed images. In one embodiment, a method for computed tomography (CT) imaging comprises reconstructing images from data acquired during a helical CT scan where table deflection parameters are estimated and the reconstruction is adjusted based on the table deflection parameters. In this way, images may be reconstructed without artifacts caused by table deflection.

Methods and systems for correcting table deflection

An imaging system includes a computed tomography (CT) acquisition unit and a processing unit. The CT acquisition unit includes an X-ray source and a CT detector configured to collect CT imaging data of an object to be imaged. The processing unit includes at least one processor operably coupled to the CT acquisition unit. The processing unit is configured to control the CT acquisition unit to collect at least one sample projection during rotation of the CT acquisition unit about the object to be imaged, compare an intensity of the at least one sample projection to an intensity of a reference projection, select a time to perform an imaging scan based on the comparison of the intensity of the at least one sample projection to the intensity of the reference projection, and control the CT acquisition unit to perform the imaging scan.

Systems and methods for imaging phase selection for computed tomography imaging

An imaging system includes a computed tomography (CT) acquisition unit and a processing unit. The CT acquisition unit includes an X-ray source and a CT detector configured to collect CT imaging data of an object to be imaged. The X-ray source and CT detector are configured to be rotated about the object to be imaged and to collect a series of views of the object as the X-ray source and CT detector rotate about the object to be imaged. The processing unit is operably coupled to the CT acquisition unit and configured to control the CT acquisition unit to vary a view duration for the views of the series. The view duration for a particular view defines an imaging information acquisition period for the particular view, wherein the series of views includes a first group of views having a first view duration and a second group of views having a second view duration that is different than the first view duration.

Systems and methods for adjustable view frequency computed tomography imaging

An imaging system includes a computer programmed to reconstruct original CT projection data, estimate noise in image space, forward project the image noise estimate to generate an initial projection noise estimate, modify the initial projection noise estimate using a statistical property of noise in projection space, remove noise in the original CT projection data by subtracting the modified noise estimate therefrom to generate noise-removed projection data, and reconstruct a final image based on the noise-removed projection data.

System and method of noise deletion in computed tomography

A method for reducing noise in a medical diagnostic image includes acquiring an initial three-dimensional (3D) volume of projection data, generating a projection space noise estimate using the 3D volume of projection data, generating an initial 3D volume of image data using the 3D volume of projection data, generating an image space noise estimate using the 3D volume of image data, generating a noise projection estimate using the projection space noise estimate and the image space noise estimate, and reconstructing an image using the generated noise estimate. A system and non-transitory computer readable medium are also described.

Methods and systems for reducing noise- related imaging artifacts

A method for reconstructing an image of an object that includes a plurality of image elements. The method includes accessing image data associated with a plurality of image elements, and reconstructing an image of the object by optimizing an objective function, where the objective function is optimized by iteratively solving a nested sequence of approximate optimization problems. The algorithm is composed of nested iterative loops, in which an inner loop iteratively optimizes an objective function approximating the outer loop objective function, and an outer loop that utilizes the solution of the inner loop to optimize the original objective function.

Method and apparatus for iterative reconstruction

A method for reconstructing an image of an object includes acquiring a set of measured projection data, reconstructing the measured projection data using a first algorithm to generate a first reconstructed image dataset, reconstructing the measured projection data using a second algorithm to generate a second reconstructed image dataset, the second algorithm being utilized to improve the temporal resolution of the second reconstructed image dataset, and generating a final image dataset using both the first and second image datasets.

Method and apparatus for reducing noise-related imaging artifacts

A tomographic system includes a gantry having an opening for receiving an object to be scanned, a radiation source, a detector positioned to receive radiation from the source that passes through the object, and a computer programmed to acquire a plurality of helical projection datasets of the object, reconstruct a first image using the acquired plurality of helical projection datasets and using a first reconstruction algorithm, reconstruct a second image using the acquired plurality of helical projection datasets and using a second reconstruction algorithm that is different from the first reconstruction algorithm, extract frequency components from each of the first and second images, sum the frequency components from each of the first and second images, and inverse transform the sum of the frequency components to generate a final image.

System and method for wide cone helical image reconstruction using blending of two reconstructions

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Madison, WI, United States of America

Guangzhi Cao