General Electric Company

Jonathan Immanuel Sperl

Christopher Judson Hardy

Luca Marinelli

Ek Tsoon Tan

Marion Irene Menzel

Kevin Franklin King

Clifford Bueno

Philip Harold Monaghan

Dirk Wim Jos Beque

Cristina Francesca Cozzini

Kinan Mahdi

A magnetic resonance imaging method includes generating spatially resolved fiber orientation distributions (FODs) from magnetic resonance signals acquired from a patient tissue using a plurality of diffusion encodings, each acquired magnetic resonance signal corresponding to one of the diffusion encodings and being representative of a three-dimensional distribution of displacement of magnetic spins of gyromagnetic nuclei present in each imaging voxel. Generating the spatially resolved FODs includes performing generalized spherical deconvolution using the acquired magnetic resonance signals and a modeled tissue response matrix (TRM) to reconstruct the spatially resolved FODs. The method also includes using the spatially resolved FODs to generate a representation of fibrous tissue within the patient tissue.

Generalized spherical deconvolution in diffusion magnetic resonance imaging

Reconstructing under-sampled PCT data includes obtaining under-sampled scan data of a subject-under-test, the object scan performed on a phase contrast computed tomography (PCT) system, performing a regularized Fourier analysis on the under-sampled scan data, correcting for one or more PCT system contributions to the under-sampled scan data by dividing the computed Fourier coefficients by Fourier coefficients representative of the one or more PCT system contributions, obtaining at least one of an absorption sinogram, a differential phase sinogram, and a dark field sinogram from the corrected Fourier coefficients, and performing tomographic reconstruction on the obtained absorption sinogram, the obtained differential phase sinogram, and the obtained dark field sinogram. A system and non-transitory computer readable medium are also disclosed.

System and method for regularized reconstruction of phase contrast computerized tomography

A method and system are provided for elementally detecting variations in density. The method includes providing a computed tomography device, comprising a radiation source, a detector, and at least one grating between the radiation source and the detector, positioning the component between the radiation source and the detector, directing radiation from the radiation source to the detector to acquire information from the component, generating at least one phase contrast image and at least one dark field contrast image of the component corresponding to variations in density with the information from the component, correlating the variations in density to a foreign mass, and displaying foreign mass distribution within the component. The system includes a radiation source, a detector, a component, a first grating, a second grating, and an analysis device capable of determining total variation of density in response to radiation received by the detector, and correlating the variation of density to free element distribution in the component.

Method for elementally detecting variations in density

Systems and methods for generating a magnetic resonance (MR) image of a tissue are provided. A method includes acquiring MR raw data. The MR raw data corresponds to MR signals obtained at undersampled q-space locations for a plurality of q-space locations that is less than an entirety of the q-space locations and the MR signals at the q-space locations represent the three dimensional displacement distribution of the spins in the imaging voxel. The method also includes performing a joint image reconstruction technique on the MR raw data to exploit structural correlations in the MR signals to obtain a series of accelerated MR images and performing, for each image pixel in each accelerated MR image of the series of accelerated MR images, a compressed sensing reconstruction technique to exploit q-space signal sparsity to identify a plurality of diffusion maps.

Diffusion spectrum imaging systems and methods

A method of regularization of x-ray phase contrast imaging (XPCi) system measurement data includes obtaining air scan data of the XPCi system prior to the presence of an object undergoing imaging, performing Fourier analysis of the air scan data, computing air coefficients from the result of the performing step, obtaining object scan data of an object undergoing imaging on the XPCi system, regularizing the object scan data, and calculating at least one of absorption image data, differential phase image data, and dark field image data by using object coefficients. A system configured to implement the method and a non-transitory computer-readable medium are disclosed.

Systems and methods for regularized Fourier analysis in x-ray phase contrast imaging

A method of compressed sensing for multi-shell magnetic resonance imaging includes obtaining magnetic resonance imaging data, the data being sampled along multi-shell spherical coordinates, the spherical coordinates coincident with a plurality of spokes that converge at an origin, constructing a symmetric shell for each respective sampled multi-shell to create a combined set of data, performing a three-dimensional Fourier transform on the combined set of data to reconstruct an image, and de-noising the reconstructed image by iteratively applying a sparsifying transform on non-sampled data points of neighboring shells. The method can also include randomly under-sampling the imaging data to create missing data points. A system configured to implement the method and a non-transitory computer readable medium are also disclosed.

Systems and methods for compressed sensing for multi-shell magnetic resonance imaging

An image reconstruction method for differential phase contrast imaging includes receiving data corresponding to a signal produced by an X-ray detector and corresponding to X-rays that passed through a subject and a grating system to reach the X-ray detector. The method also includes performing a fringe analysis on the received data. The fringe analysis includes a non-integer fringe fraction correction utilizing one or more adapted basis functions in the Fourier domain to determine one or more Fourier coefficients. A differential phase image of the subject is generated by utilizing the one or more Fourier coefficients.

Image reconstruction methods for differential phase contrast X-ray imaging

A phase retrieval method for differential phase contrast imaging includes receiving data corresponding to a differential phase image generated from a measured signal. The measured signal corresponds to an X-ray signal detected by a detector after passing through a subject located with a grating arrangement between an X-ray source and the detector. The method further includes generating a phase image corresponding to the integration of the differential phase image. Generating the phase image includes performing an iterative total variation regularized integration in the Fourier domain.

Image reconstruction method for differential phase contrast X-ray imaging

A magnetic resonance (MR) imaging method includes acquiring MR signals having phase and magnitude at q-space locations using a diffusion sensitizing pulse sequence performed on a tissue of interest, wherein the acquired signals each include a set of complex Fourier encodings representing a three-dimensional displacement distribution of the spins in a q-space location. The signals each include information relating to coherent motion and incoherent motion in the q-space location. The method also includes determining a contribution by coherent motion to the phase of the acquired MR signals; removing the phase contribution attributable to coherent motion from the acquired MR signals to produce a complex data set for each q-space location and an image of velocity components for each q-space location; and producing a three-dimensional velocity image from the image of the velocity components.

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Freising, Germany

Jonathan Immanuel Sperl