General Electric Company

Indian Institute of Technology Delhi

University of Rochester

Kedar Bhalchandra Khare

Christopher Judson Hardy

Jeffrey Wayne Eberhard

Bernhard Erich Hermann Claus

Luca Marinelli

Kevin Franklin King

Bruno Kristiaan Bernard De Man

Yves Lucien Trousset

David Allen Langan

Jens Rittscher

Joseph Manak

Nicholas A George

Hao Lai

Cyril Riddell

Xiaodong Tao

Joby Joseph

Samsheerali Pothiyil Thottiparambil

Manoj Kumar Sharma

Paramasivam Senthilkumaran

Techniques described herein are generally related to non-interferometric phase measurements of an optical signal. The various described techniques may be applied to methods, systems, devices or combinations thereof. Some methods for determining phase data of the optical signal may include transmitting the optical signal through a first optical element and obtaining first intensity data at a first focal plane of the first optical element by an optical sensor. Example methods may also include transmitting the optical signal through a second optical element. The second optical element may include a phase transformation mask. Example methods may further include obtaining a second intensity data at a second focal plane of the second optical element by the optical sensor and determining the phase data for the optical signal based on the first intensity data and the second intensity data.

Non-interferometric phase measurement

Systems, methods and non-transitory computer readable media for imaging. The system includes one or more radiation sources and detectors configured to transmit x-ray radiation towards a subject for imaging a dynamic process in a ROI of the subject and to acquire projection data corresponding to the ROI, respectively. The system also includes a computing device operatively coupled to one or more of the radiation sources and the detectors. The computing device is configured to provide control signals for performing one or more reference scans for acquiring reference data from a plurality of angular positions around the subject and for performing one or more tomosynthesis scans using one or more tomosynthesis trajectories for acquiring tomosynthesis data following the onset of the dynamic process. Additionally, the computing device is configured to reconstruct one or more images representative of the dynamic process using the reference data and/or the tomosynthesis data.

Systems and methods for imaging dynamic processes

Techniques described herein are generally related to high resolution image recovery of objects from digital holograms. The various described techniques may be applied to methods, systems, devices or combinations thereof. Some described methods for recovering an image may include receiving reference beam data that corresponds to a reference interference pattern and receiving hologram data corresponding to an object. The method may also include applying a cost function to the hologram data and the reference beam data to determine the object image data associated with the object. The cost function may include a smoothness constraint applied to the object image data. The cost function can be iteratively reduced to obtain object image data corresponding to the object and the obtained object image data can be processed to recover the image of the object from single shot holograms with image resolution greater than conventional holographic imaging system.

Image recovery from single shot digital hologram

The subject matter disclosed herein relates to X-ray imaging systems, and more specifically to digital X-ray imaging systems. In one embodiment, an imaging system includes an X-ray source configured to emit X-rays. The imaging system also includes an X-ray detector configured to detect the emitted X-rays and produce a corresponding electrical signal. The imaging system also includes a gantry configured to at least partially revolve the X-ray source and the X-ray detector about a primary rotational axis. The X-ray detector is coupled to the gantry so that a diagonal of the X-ray detector is oriented substantially perpendicular to the primary rotational axis.

System and method for orienting an X-ray detector

A signal processing method is provided. The signal processing method includes the steps of generating undersampled data corresponding to an object, determining a variable thresholding parameter based on a composition of the undersampled data, and iteratively determining thresholded coefficients to generate a plurality of coefficients by utilizing the undersampled data, a current solution and the variable thresholding parameter by updating the variable thresholding parameter and the current solution, and reconstructing a data signal using the plurality of coefficients.

System and method for processing data signals

Embodiments of the invention are directed to a new type of phase screen, i.e., an opto-electronic device that can convert a distorted incoming optical wavefront into a plane wave or, conversely, transform a plane wave into a prescribed varying output wavefront. The basic concept involves novel binary all-digital MEMS interferometer configurations that can be used to create controlled and arbitrary optical wavefront using only 0,1 amplitude changes followed by differential propagation distances to convert these amplitude variations into controllable and/or continuous phase variations. Clustered pixel notions, such as Floyd-Steinberg, Stucki or other algorithms useful in digital half-tone printing, are simultaneously employed to create controllable grey-level variations as well as continuous phase variations. Desired grey-levels can be obtained wherein each pixel is formed by, e.g., a 3&#xd7;3 or 5&#xd7;5 cluster of mirrors. Both the filling-in of the outputs of the binary mirror (0,1) and the grey-levels are accomplished simply by spatial averaging over a short propagation distance.

Digital binary MEMS wavefront control

A signal processing method is presented. The method includes acquiring undersampled data corresponding to an object, initializing a first image solution and a second image solution, determining a linear combination solution based upon the first image solution and the second image solution, generating a plurality of selected coefficients by iteratively updating the first image solution, the second image solution and the linear combination solution and adaptively thresholding one or more transform coefficients utilizing the undersampled data, an updated first image solution, an updated second image solution and an updated linear combination solution, and reconstructing a data signal using the plurality of selected coefficients.

Systems and method for reconstruction of x-ray images are provided. One method includes acquiring a plurality of image views using an x-ray imaging system, the plurality of image views defining a limited tomographic dataset. The method also includes performing three-dimensional (3D) image reconstruction using the plurality of image views in an iterative reconstruction, wherein the iterative reconstruction includes forming a linear combination based on a plurality of previous iteration results. The method further includes displaying an image based on the image reconstruction, wherein the image includes clinically relevant high-frequency detail information.

System and method for reconstruction of X-ray images

A tomographic imaging apparatus is provided for generating images. The tomographic apparatus includes a computer programmed to access a data sinogram representative of the image, reconstruct the image, divide the image into a plurality of sub-regions, define a region of interest including at least one sub-region, reprojecting a region of interest or a complement of the region of interest to generate a region of interest sinogram or a sinogram representative of the complement of the region of interest and reconstructing a resultant sinogram using iterative methods to generate an image.

System and method for image reconstruction

A signal processing method include steps initializing a residual data signal representative of an acquired data signal, determining a significant coefficient corresponding to the residual data signal, updating the residual data signal using the significant coefficient to generate updated residual data signal, iteratively determining significant coefficients to generate a plurality of significant coefficients using the updated residual data signal, updating the plurality of significant coefficients by using a successive approximation technique, to improve the numerical accuracy of the significant coefficients and reconstructing a data signal using the updated plurality of significant coefficients.

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New Delhi, India

Kedar Bhalchandra Khare