General Electric Company

Purdue Research Foundation

University of Notre Dame Du Lac

Kai Zeng

Jed Douglas Pack

Bruno Kristiaan Bernard De Man

Zhye Yin

Jean-Baptiste Thibault

Bruno Kristiaan Bernard DeMan

Jiang Hsieh

Charles Addison Bouman

Ken David Sauer

Zhou Yu

Kyle Morgan Champley

Brian Edward Nett

Jiahua Fan

Lin Fu

Debashish Pal

Paulo Ricardo Dos Santos Mendonca

Paulo Ricardo Mendonca

Thomas Matthew Benson

Guangzhi Cao

Evgeny Drapkin

Adam Budde

Roy Arnulf Helge Nilsen

Jean-Baptiste Daniel Marie Thibault

Approaches for acquiring CT image data corresponding to a full scan, but at a reduced dose are disclosed. In one implementation, X-ray tube current modulation is employed to reduce the effective dose. In other implementations, acquisition of sparse views, z-collimation, and two-rotation acquisition protocols may be employed to achieve a reduced dose relative to a full-scan acquisition protocol.

Method and system for reduced dose X-ray imaging

Methods and systems are provided for correcting artifacts in iterative reconstruction processes. In certain embodiments, weighting schemes may be applied such that less than all of the available scan or projection data is utilized in the iterative reconstruction. In this manner, inconsistencies in the data undergoing reconstruction may be reduced.

Method and system for correcting artifacts in image reconstruction

A system and method for CT projection extrapolation are provided. The method comprises receiving a CT projection for extrapolation. The method also comprises selecting a target patch comprising at least one pixel of a row to be extrapolated. The method further comprises generating a correlation profile between the target patch and one or more source patches, wherein the source patches comprise measured pixels in the CT projection in one or more rows adjacent to the target patch. The projection data is generated for at least one pixel of the target patch based on the correlation profile and the measured pixels of at least one of the source patches.

Methods and systems for CT projection domain extrapolation

An approach is disclosed for acquiring multi-sector computed tomography scan data. The approach includes activating an X-ray source during heartbeats of a patient to acquire projection data over a limited angular range for each heartbeat. The projection data acquired over the different is combined. An image having good temporal resolution is reconstructed using the combined projection data.

Multi-sector computed tomography image acquisition

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

Approaches for performing computed tomographic image reconstruction are described. In one embodiment, a full or almost full scan of scan data is acquired and a plurality of image reconstructions are performed based on the scan data, wherein the plurality of image reconstructions result in a corresponding plurality of image volumes wherein the image reconstructions use different view weighting functions. Further, the present approaches provide for combining the plurality of image volumes together to produce a final image volume.

Computed tomography image reconstruction

Approaches are described for processing half-scan or full-scan cone beam image data using one or more half-ramp filtering operations. In one embodiment, the half-ramp filtering operations allow extraction and use of missing frequency data so as to generate a reconstructed image that is relatively complete in terms of frequency data and which has suitable temporal resolution. In addition, in certain embodiments, the reconstructed image may have uniform frequency weighting.

Method and system for reconstruction of tomographic images

Approaches are described for generating an initial reconstruction of CT data acquired using a wide-cone system. In one implementation, frequency data may be patched in to a first scan, such as an axial scan, from a second scan, such as a helical scan. In one embodiment, an initial reconstruction may be processed (such as via a non-linear operation) to correct frequency omissions and/or errors in the reconstruction. Corrected frequency information may be utilized to improve the reconstructed image.

A system and method include acquisition of a set of image data corresponding to a time period of data acquisition, the set of image data corresponding to a plurality of voxels, wherein each of the plurality of voxels corresponds to a distinct acquisition time within the time period of data acquisition. The system and method further include the modeling of the plurality of voxels as a function of time based on a plurality of kinetic parameters associated therewith and reconstruction of an image from the set of image data based on the modeled plurality of voxels.

System and method of iterative image reconstruction for computed tomography

An improved iterative reconstruction method to reconstruct a first image includes generating an imaging beam, receiving said imaging beam on a detector array, generating projection data based on said imaging beams received by said detector array, providing said projection data to an image reconstructor, enlarging one of a plurality of voxels and a plurality of detectors of the provided projection data, reconstructing portions of the first image with the plurality of enlarged voxels or detectors, and iteratively reconstructing the portions of the first image to create a reconstructed image.

Iterative reconstruction

Algorithms are disclosed that recombine acquired data so as to generate a substantially uniform and complete set of frequency data where frequency data might otherwise be incomplete. This process, or its equivalent, may be accomplished in a computationally efficient manner using filtering steps in one or both of the reconstruction space and/or the post-processing space.

Reconstruction of projection data to generate tomographic images having improved frequency characteristics

Approaches are described for generating an initial reconstruction of CT data acquired using a wide-cone system. The initial reconstruction may be processed (such as via a non-linear operation) to correct frequency omissions and/or errors in the reconstruction. Corrected frequency information may then be added to the reconstruction to improve the reconstructed image.

A method of performing a computed tomographic image reconstruction is provided. The method provides for performing a short scan of an imaging object to acquire a short scan data, performing a plurality of image reconstructions based on the short scan data wherein the plurality of image reconstructions result in a corresponding plurality of image volumes wherein the image reconstructions use different view weighting functions, filtering the plurality of image volumes such that when the volumes are added together, the frequency domain data is substantially uniformly weighted. Further, the method provides for combining the plurality of image volumes together to produce a final image volume.

System and method for image reconstruction

In one embodiment, a first set of projection data is acquired using a first portion of a detector and a second set of projection data is acquired using a second portion of the detector. The second set of projection data is supplemented based upon the first set of projection data to generate a supplemented set of projection data. A volumetric image may be generated using the supplemented set of projection data.

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Clifton Park, NY, United States of America

Kai Zeng