University of Central Florida Research Foundation, Inc.

Itomography Corporation

Canon Medical Systems Corporation

Kabushiki Kaisha Toshiba

General Electric Company

Toshiba Medical Systems Corporation

Virginia Tech Intellectual Properties, Inc.

Perkinelmer Health Sciences, Inc.

Toshiba Medical Research Institute USA

Alexander Katsevich

Michael A Frenkel

Zhou Yu

Igor Frenkel

Michael D Silver

Alexander A Zamyatin

Seongjin Yoon

Jiang Hsieh

Ge Wang

Samit Kumar Basu

Wenli Wang

Jun Zhao

Qiulin Tang

Daxin Shi

Yang Lu

Hengyong Yu

Michael Frenkel

Victor Prieto

Airidas Korolkovas

Jeff Meganck

In various embodiments, the present invention provides a multi-modality imaging system in combination with a novel imaging method comprising complex modeling of the modalities and machine learning. In a particular embodiment, multi-modality imaging of a large rock core is described.

System and method using tomographic multi-modality three-dimensional imaging to estimate medium parameters

In various embodiments, the present invention provides an improved system and method for motion estimation and motion compensation in cone beam computer tomography (CBCT). The present invention utilizes a method for alternating minimization between volume and motion sub-iterations and results in an improved system and method for motion estimation and compensation in CBCT.

Motion estimation and compensation in cone beam computed tomography (CBCT)

A method and apparatus is provided to reconstruct a computed tomography image using iterative reconstruction (IR) that is accelerated using various combinations of ordered subsets, conjugate gradient, preconditioning, resetting/restarting, and/or gradient approximation techniques. For example, when restarting criteria are satisfied the IR algorithm can be reset by setting conjugate-gradient parameters to initial values and/or by changing the number of ordered subsets. The IR algorithm can be accelerated by approximately calculating the gradients, by using a diagonal or Fourier preconditioner, and by selectively updating the preconditioner based on the regularization function. The update direction and step size can be calculated using the preconditioner and a surrogate function, which is not necessarily separable.

Method and apparatus for acceleration of iterative reconstruction of a computed tomography image

An apparatus and method are provided for computed tomography (CT) imaging to reduce truncation artifacts due to a part of an imaged object being outside the scanner field of view (FOV) for at least some views of a CT scan. After initial determining extrapolation widths to extend the projection data to fill a truncation region, the extrapolation widths are combined into a padding map and smoothed to improve uniformity and remove jagged edges. Then a hybrid material model fits the measured projection data nearest the truncation region to extrapolate projection data filling the truncation region. Smoothing the padding map is improved by the insight that in general smaller extrapolation widths are more accurate and trustworthy. Further, practical applications often include multiple inhomogeneous materials. Thus, the hybrid material model provides a better approximation than single material models, and more accurate fitting is achieved.

Method and apparatus for projection domain truncation correction in computed-tomography (CT)

An improved system and method for estimating and compensating for motion by reducing motion artifacts produced during image reconstruction from helical computed tomography (CT) scan data. In a particular embodiment, the reconstruction may be based on helical partial angle reconstruction (PAR) and the registration may be performed utilizing one or more artificial intelligence (AI) based methods.

System and method for motion estimation using artificial intelligence in helical computed tomography

Described herein are systems and methods for automated completion, combination, and completion by combination of sinograms. In certain embodiments, sinogram completion is based on a photographic (e.g. spectral or optical) acquisition and a CT acquisition (e.g., micro CT). In other embodiments, sinogram completion is based on two CT acquisitions. The sinogram to be completed may be truncated due to a detector crop (e.g., a center-based crop or an offset based crop). The sinogram to be completed may be truncated due to a subvolume crop (e.g., based on low resolution image projected onto sinogram).

Systems and methods for automated sinogram completion, combination, and completion by combination

An improved system and method for estimating and compensating for motion by reducing motion artifacts produced during image reconstruction from helical computed tomography (CT) scan data. In a particular embodiment, the reconstruction may be based on helical partial angle reconstruction (PAR).

System and method for motion estimation and compensation in helical computed tomography

Systems, apparatus and methods for collecting, storing, processing, reconstructing, and interpreting raw scan data from a medical diagnostic imaging scan. Raw data after a scan such as a Computed Tomography (CT) scan is sent to a raw scan database system and image reconstruction system, where image volumes are reconstructed using software from the software bank and sent to a data management system. Raw scan data generated once by a scanner is continuously used at later times to reconstruct images of the patient without having to perform additional patient scans.

Systems, apparatus and methods for collecting and storing raw scan data and software for performing data processing, image reconstruction and interpretation

Methods, processes and systems of image reconstruction utilizing a hybrid local tomography (HLT) methodology for reconstructing internal body images in medical applications, and the like. The system and method of the present invention provides an image with emphasized edges, and the image provides estimations of the attenuation coefficient inside the object being scanned.

System and method for hybrid local tomography image reconstruction

The methods and systems of the present invention is an algorithm which estimates motion inside objects that change during the scan. The algorithm is flexible and can be used for solving the misalignment correction problem and, more generally, for finding scan parameters that are not accurately known. The algorithm is based on Local Tomography so it is faster and is not limited to a source trajectory for which accurate and efficient inversion formulas exist.

Method for estimating scan parameters from tomographic data

Methods, processes and systems of image reconstruction using variable filter length local tomography, for reconstructing internal body images in medical applications, and the like. The system and method of the present invention utilizes less radiation and less computer power than the prior art, without using iteration algorithms so that all target sizes from large to small can be reconstructed.

System and method of variable filter length local tomography

Algorithm for motion estimation from the tomographic data

Methods, processes and systems of image reconstruction using variable filter length local tomography, for reconstructing internal body images in medical applications, and the like. Algorithm uses less radiation, less computer power than prior art, and without using iteration algorithms so that all target sizes from large to small can be reconstructed.

Variable filter length local tomography

The present invention provides systems, methods, and devices for improved computed tomography (CT). More specifically, the present invention includes methods for improved cone-beam computed tomography (CBCT) resolution using improved filtered back projection (FBP) algorithms, which can be used for cardiac tomography and across other tomographic modalities. Embodiments provide methods, systems, and devices for reconstructing an image from projection data provided by a computed tomography scanner using the algorithms disclosed herein to generate an image with improved temporal resolution.

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Oviedo, FL, United States of America

Alexander Katsevich