General Electric Company

Ge Medical Systems Global Technology Company, LLC

Nview Medical Inc.

Dimitri Victorovich Yatsenko

Steven Emerson Curtis

Jon Thomas Lea

Richard Larry Anderton

Charles Frederick Lloyd

Cristian Atria

J Joseph Allred

Daniel Mahonri Bates

Nisha Ramesh

A system and method for reconstructing an image of a target object using an iterative reconstruction technique can include a machine learning model as a regularization filter (). An image data set for a target object generated using an imaging modality can be received, and an image of the target object can be reconstructed using an iterative reconstruction technique that includes a machine learning model as a regularization filter () used in part to reconstruct the image of the target object. The machine learning model can be trained prior to receiving the image data using learning datasets that have image data associated with the target object, where the learning datasets providing objective data for training the machine learning model, and the machine learning model can be included in the iterative reconstruction technique to introduce the object features into the image of the target object being reconstructed.

Image reconstruction using machine learning regularizers

A system for and a method of controlling a spatial distribution of radiation intensity in a beam of radiation is provided. The system includes a control device located to receive the initial beam of radiation from the radiation source. The control device includes a first radiation absorbing structure located at a position in generally superposing alignment relative a position of a second radiation absorbing structure. Each first and second radiation absorbing structure is operable to independently articulate. The modulator configuration signal is operable to cause adjustment of the position of at least one of the first and second radiation absorbing structures relative to the other so as to selectively adjust a spatial distribution of radiation intensity of a modulated beam.

Method and system for controlling radiation intensity of an imaging system

Certain embodiments of the present invention provide a method and system for improved calibration of an image acquisition device. Certain embodiments of the system include an image acquisition device for obtaining at least one image of an object and a calibration fixture positioned in relation to the image acquisition device. The calibration fixture includes a radiotranslucent material providing low frequency content for characterizing the image acquisition device. In an embodiment, the calibration fixture includes a plurality of peaks and valleys to create a low frequency signal for characterizing the image acquisition device. The calibration fixture may be positioned between the image acquisition device and an energy source such that a distance between the image acquisition device and the calibration fixture is minimized. In certain embodiments, a grating or other calibration fixture may be used to generate a moir&#xe9; pattern to calibrate the image acquisition device.

System and method for integration of a calibration target into a C-arm

Certain embodiments of the present invention provide a system and method for reducing image noise with the use of a minimal error spatiotemporal recursive filter. An input image is filtered both temporally and spatially, producing a temporal output and a spatial output. Both the temporal output and the spatial output are correlated with the input image to produce a temporal correlation output and a spatial correlation output. The temporal correlation output and the spatial correlation output are mixed to generate a selecting signal. The selecting signal directly or indirectly determines the composition of an output image. The selecting signal may select a portion of the temporal output and a portion of the spatial output to compose an output image. Alternatively, the selecting signal may select either the temporal output or the spatial output to compose an output image.

System and method for image noise reduction using a minimal error spatiotemporal recursive filter

Methods and systems for controlling exposure for medical imaging devices is provided. The method includes varying the exposure level of X-rays within an X-ray imaging system to generate a plurality of images having different exposure levels and combining the plurality of images in an additive process to form a single X-ray image.

Methods and systems for controlling exposure for medical imaging devices

The present invention provides for an x-ray system and method using dynamic automated spatial modulation of an x-ray beam. The system includes an x-ray source transmitting a spatially modulated beam towards an object to be imaged, an x-ray detector receiving the beam and measuring a plurality of intensities across the beam, a beam processor controlling the beam intensity profile, and an image processor producing an output image signal. The detector produces a residual image based on at least the intensities measured at the detector. The beam intensity profile may be based on at least some of the following: (a) the residual image from the x-ray detector, (b) current beam intensities, (c) regions on interest in the image, and (d) predicted or measured object motion in the image. The system's output image is based on one or more of said residual image and said beam intensity signal.

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Salt Lake City, UT, United States of America

Dimitri Victorovich Yatsenko