Rensselaer Polytechnic Institute

General Electric Company

Yan Xi

Ge Wang

Wenxiang Cong

Bruno Kristiaan Bernard De Man

Yannan Jin

Jun Zhao

Zaifeng Shi

Mianyi Chen

Systems and method for performing X-ray computed tomography (CT) that can improve spectral separation and decrease motion artifacts without increasing radiation dose are provided. The systems and method can be used with either a kVp-switching source or a single-kVp source. When used with a kVp-switching source, an absorption grating and a filter grating can be disposed between the X-ray source and the sample to be imaged. Relative motion of the filter and absorption gratings can by synchronized to the kVp switching frequency of the X-ray source. When used with a single-kVp source, a combination of absorption and filter gratings can be used and can be driven in an oscillation movement that is optimized for a single-kVp X-ray source. With a single-kVp source, the absorption grating can also be omitted and the filter grating can remain stationary.

Rapid filtration methods for dual-energy X-ray CT

Novel and advantageous systems and method for obtaining and/or reconstructing simultaneous computed tomography (CT)-magnetic resonance imaging (MRI) images are provided. Structural coupling (SC) and compressive sensing (CS) techniques can be combined to unify and improve CT and MRI reconstruction. A bidirectional image estimation method can be used to connect images from different modalities, with CT and MRI data serving as prior knowledge to each other to produce better CT and MRI image quality than would be realized with individual reconstruction.

Simultaneous CT-MRI image reconstruction

Systems and methods for geometric calibration and image reconstruction in computed tomography (CT) scanning using iterative reconstruction algorithms are provided. An iterative reconstruction algorithm can be used to reconstruct an improved image, and then the improved image can be used to adjust inaccurate parameters by using a Locally Linear Embedding (LLE) method. Adjusted parameters can then be used to reconstruct new images, which can then be used to further adjust the parameters. The steps of this iterative process can be repeated until a quality threshold is met.

Automatic system calibration  method of X-ray CT

Novel and advantageous methods and systems for performing spectral computed tomography are provided. An edge-on detector, such as a silicon strip detector, can be used to receive X-rays after passing through a sample to be imaged. An energy resolving process can be performed on the collected X-ray radiation. The CT scanner can have third-generation or fourth-generation geometry.

Spectral CT systems and methods

Systems and methods for X-ray phase-contrast imaging (PCI) are provided. A quasi-periodic phase grating can be positioned between an object being imaged and a detector. An analyzer grating can be disposed between the phase grating and the detector. Second-order approximation models for X-ray phase retrieval using paraxial Fresnel-Kirchhoff diffraction theory are also provided. An iterative method can be used to reconstruct a phase-contrast image or a dark-field image.

X-ray phase-contrast imaging

A method includes receiving, with at least one processor, a first projection dataset corresponding to X-rays at a first energy level projected towards a subject at a first set of view angles and receiving, with the at least one processor, a second projection dataset corresponding to X-rays at a second energy level projected towards the subject at a second set of view angles. The method further includes identifying, with the at least one processor, a metal trace from at least one of the first projection dataset and the second projection dataset. Moreover, the method includes converting, with the at least one processor, at least a portion of the first projection dataset to a pseudo dataset at the second energy level. The method also includes generating, with the at least one processor, a final image of the subject based on the second projection dataset, the pseudo dataset, and the metal trace.

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Syracuse, NY, United States of America

Yan Xi