General Electric Company

University of Michigan

Purdue Research Foundation

University of Notre Dame Du Lac

Debashish Pal

Jean-Baptiste Thibault

Zhou Yu

Jiang Hsieh

Bruno Kristiaan Bernard De Man

Brian Edward Nett

Lin Fu

Jeffrey Allen Fessler

Charles Addison Bouman

Ken David Sauer

Somesh Srivastava

Paavana Sainath

Sathish Ramani

Roshni Bhagalia

Evgeny Drapkin

Donghwan Kim

Madison Gray McGaffin

Jang Hwan Cho

Kai Zeng

Hewei Gao

Guangzhi Cao

Jie Tang

Girijesh Kumar Yadava

Basel Taha

Ruoqiao Zhang

Hung Nien

Kriti Sen Sharma

Ryan Thome

Pavaana Sainath

Basel Hasan Taha

As set forth herein low energy signal data and high energy signal data can be acquired. A first material decomposed (MD) image of a first material basis and a second material decomposed (MD) image of a second material basis can be obtained using the low energy signal data and the high energy signal data. At least one of the first or second MD image can be input into a guide filter for output of at least one noise reduced and cross-contamination reduced image. A computed tomography (CT) imaging system can be provided that includes an X-ray source and a detector having a plurality of detector elements that detect X-ray beams emitted from the X-ray source. Low energy signal data and high energy signal data can be acquired using the detector.

Guided filter for multiple level energy computed tomography (CT)

A method for iteratively reconstructing an image is provided. The method includes acquiring, with a detector, computed tomography (CT) imaging information. The method also includes generating, with at least one processor, sinogram information from the CT imaging information. Further, the method includes generating, with the at least one processor, image domain information from the CT imaging information. Also, the method includes updating the image using the sinogram information. The method further includes updating the image using the image domain information. Updating the image using the sinogram information and updating the image using the image domain information are performed separately and alternately in an iterative fashion.

Systems and methods for parallel processing of imaging information

A framework for an iterative reconstruction algorithm is described which combines two or more of an ordered subset method, a preconditioner method, and a nested loop method. In one type of implementation a nested loop (NL) structure is employed where the inner loop sub-problems are solved using ordered subset (OS) methods. The inner loop may be solved using OS and a preconditioner method. In other implementations, the inner loop problems are created by augmented Lagrangian methods and then solved using OS method.

Accelerated iterative reconstruction

Various methods and systems for spectral computed tomography imaging are provided. In one embodiment, a method comprises acquiring a first projection dataset and a second projection dataset, detecting a location of metal in the first projection dataset, applying corrections to the first and second projection datasets based on the location of the metal, and displaying an image reconstructed from the corrected first and second projection datasets. In this way, metal artifacts may be substantially reduced in dual or multi-energy CT imaging.

Methods and systems for metal artifact reduction in spectral CT imaging

A method includes obtaining spectral computed tomography (CT) information via an acquisition unit having an X-ray source and a CT detector. The method also includes, generating, with one or more processing units, using at least one image transform, a first basis image and a second basis image using the spectral CT information. Further, the method includes performing, with the one or more processing units, guided processing on the second basis image using the first basis image as a guide to provide a modified second basis image. Also, the method includes performing at least one inverse image transform using the first basis image and the modified second basis image to generate at least one modified image.

Systems and methods for guided de-noising for computed tomography

The use of the channelized preconditioners in iterative reconstruction is disclosed. In certain embodiments, different channels correspond to different frequency sub-bands and the output of the different channels can be combined to update an image estimate used in the iterative reconstruction process. While individual channels may be relatively simple, the combined channels can represent complex spatial variant operations. The use of channelized preconditioners allows empirical adjustment of individual channels.

Iterative reconstruction in image formation

An imaging system includes a rotatable gantry for receiving an object to be scanned, a generator configured to energize an x-ray source to generate x-rays, a detector positioned to receive the x-rays that pass through the object, and a computer. The computer is programmed to obtain knowledge of a metal within the object, scan the object using system scanning parameters, reconstruct an image of the object using a reconstruction algorithm, and automatically select at least one of the system scanning parameters and the reconstruction algorithm based on the obtained knowledge.

System and method for reducing high density artifacts in computed tomography imaging

A method is provided. The method includes acquiring a first dataset at a first energy spectrum and a second dataset at a second energy spectrum. The method also includes extracting a metal artifact correction signal using the first dataset and the second dataset or using a first reconstructed image and a second reconstructed image generated respectively from the first and the second datasets. The method further includes performing metal artifact correction on the first reconstructed image using the metal artifact correction signal to generate a first corrected image.

System and method for correcting for metal artifacts using multi-energy computed tomography

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 is provided for iteratively reconstructing an image of an object. The method includes accessing measurement data associated with the image, and using a simultaneous algorithm to reconstruct the image. Using the simultaneous algorithm to reconstruct the image includes determining a scaling factor that is voxel-dependent, and applying the voxel-dependent scaling factor to a gradient of an objective function to reconstruct the image.

A method is provided for reconstructing an image of an object that includes image elements. The method includes accessing measurement data associated with the image elements, introducing an auxiliary variable to transform an original problem of reconstructing the image to a constrained optimization problem, and solving the constrained optimization problem using a method of multipliers to create a sequence of sub-problems and solve the sequence of sub-problems. Solving the sequence of sub-problems includes reconstructing the image by optimizing a first objective function. The first objective function is optimized by iteratively solving a nested sequence of approximate optimization problems. An inner loop iteratively optimizes a second objective function approximating the first objective function. An outer loop utilizes the solution of the second objective function to optimize the first objective function.

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. The computer is programmed to acquire a plurality of projection datasets of the object, define a temporal subset of projection datasets from the plurality of projection datasets, reconstruct a working image of the object using the plurality of projection datasets, identify a region of motion in the working image, and minimize motion artifacts in the region of motion in the working image using the temporal subset of projection datasets.

Growing community of inventors

Waukesha, WI, United States of America

Debashish Pal