Abstract: Image security is becoming an increasingly important issue with the progress of deep learning based image manipulations, such as deep image inpainting and deep fakes. There has been considerable work to date on detecting such image manipulations using better and better algorithms, with little attention being paid to the possible role hardware advances may have for more powerful algorithms. This disclosure proposes to use a focal stack camera as a novel secure imaging device for localizing inpainted regions in manipulated images. Applying convolutional neural network (CNN) methods to focal stack images achieves significantly better detection accuracy compared to single image based detection.

Abstract: A system and method for acquiring image data from an object that includes a plurality of spins is described. A magnetic field is applied to the object to align the spins along a longitudinal axis. A first pulse is applied to the spins for rotating the spins from the longitudinal axis toward a transverse plane. Image data is acquired from the spins during a free precession interval in which the spins precess in the transverse plane. A second pulse is applied to the spins for rotating the spins from the transverse plane to at least substantially along the longitudinal axis. At least one of the first and second pulses is spectrally or spectrally-spatially designed.

Abstract: A light field imaging system with transparent photodetectors is presented. The light field imaging system includes: a stack of two or more detector planes, an imaging optic, and an image processor. The detector planes include one or more transparent photodetectors, such that transparent photodetectors have transparency greater than fifty percent (at one or more wavelengths) while simultaneously exhibiting responsivity greater than one amp per watt. The imaging optic is configured to receive light rays from a scene and refract the light rays towards the stack of two or more detector planes, such that the refracted light rays pass through the transparent detector planes and the refracted light rays are focused within the stack of detector planes. The image processor reconstruct a light field for the scene (at one of more wavelengths) using the light intensity distribution measured by each of the photodetectors.

Abstract: A method for iteratively reconstructing an image is provided. The method includes acquiring, with a detector, computed tomography (CT) imaging information. The method also includes generating, with at least one processor, sinogram information from the CT imaging information. Further, the method includes generating, with the at least one processor, image domain information from the CT imaging information. Also, the method includes updating the image using the sinogram information. The method further includes updating the image using the image domain information. Updating the image using the sinogram information and updating the image using the image domain information are performed separately and alternately in an iterative fashion.

Abstract: Methods, systems, and non-transitory computer readable media for image reconstruction are presented. Measured data corresponding to a subject is received. A preliminary image update in a particular iteration is determined based on one or more image variables computed using at least a subset of the measured data in the particular iteration. Additionally, at least one momentum term is determined based on the one or more image variables computed in the particular iteration and/or one or more further image variables computed in one or more iterations preceding the particular iteration. Further, a subsequent image update is determined using the preliminary image update and the momentum term. The preliminary image update and/or the subsequent image update are iteratively computed for a plurality of iterations until one or more termination criteria are satisfied.

Abstract: A system and method for acquiring image data from an object that includes a plurality of spins is described. A magnetic field is applied to the object to align the spins along a longitudinal axis. A first pulse is applied to the spins for rotating the spins from the longitudinal axis toward a transverse plane. Image data is acquired from the spins during a free precession interval in which the spins precess in the transverse plane. A second pulse is applied to the spins for rotating the spins from the transverse plane to at least substantially along the longitudinal axis. At least one of the first and second pulses is spectrally or spectrally-spatially designed.

Abstract: A method is provided for iteratively reconstructing an image of an object. The method includes accessing measurement data associated with the image, and using a simultaneous algorithm to reconstruct the image. Using the simultaneous algorithm to reconstruct the image includes determining a scaling factor that is voxel-dependent, and applying the voxel-dependent scaling factor to a gradient of an objective function to reconstruct the image.

Abstract: Methods provided for forward and back-projection, which are referred to as separable footprint (SF) projectors: exemplified by the SF-TR and SF-TT projectors. These methods approximate the voxel footprint functions as 2D separable functions. Because of the separability of these footprint functions, calculating their integrals over a detector cell is greatly simplified and can be implemented efficiently. In some embodiments, the SF-TR projector uses trapezoid functions in the transaxial direction and rectangular functions in the axial direction. In some embodiments, the SF-TT projector uses trapezoid functions in both the axial and transaxial directions. Simulations and experiments showed that both SF projector methods are more accurate than conventional distance-driven (DD) projectors. Moreover, the SF-TT projector is more accurate than the SF-TR projector for rays associated with large cone angles.

Abstract: A method is provided for reconstructing an image of an object that includes image elements. The method includes accessing measurement data associated with the image elements, introducing an auxiliary variable to transform an original problem of reconstructing the image to a constrained optimization problem, and solving the constrained optimization problem using a method of multipliers to create a sequence of sub-problems and solve the sequence of sub-problems. Solving the sequence of sub-problems includes reconstructing the image by optimizing a first objective function. The first objective function is optimized by iteratively solving a nested sequence of approximate optimization problems. An inner loop iteratively optimizes a second objective function approximating the first objective function. An outer loop utilizes the solution of the second objective function to optimize the first objective function.

Abstract: Methods, systems, and non-transitory computer readable media for image reconstruction are presented. Measured data corresponding to a subject is received. A preliminary image update in a particular iteration is determined based on one or more image variables computed using at least a subset of the measured data in the particular iteration. Additionally, at least one momentum term is determined based on the one or more image variables computed in the particular iteration and/or one or more further image variables computed in one or more iterations preceding the particular iteration. Further, a subsequent image update is determined using the preliminary image update and the momentum term. The preliminary image update and/or the subsequent image update are iteratively computed for a plurality of iterations until one or more termination criteria are satisfied.

Abstract: A method is provided for reconstructing an image of an object that includes image elements. The method includes accessing measurement data associated with the image elements, introducing an auxiliary variable to transform an original problem of reconstructing the image to a constrained optimization problem, and solving the constrained optimization problem using a method of multipliers to create a sequence of sub-problems and solve the sequence of sub-problems. Solving the sequence of sub-problems includes reconstructing the image by optimizing a first objective function. The first objective function is optimized by iteratively solving a nested sequence of approximate optimization problems. An inner loop iteratively optimizes a second objective function approximating the first objective function. An outer loop utilizes the solution of the second objective function to optimize the first objective function.

Abstract: A method is provided for iteratively reconstructing an image of an object. The method includes accessing measurement data associated with the image, and using a simultaneous algorithm to reconstruct the image. Using the simultaneous algorithm to reconstruct the image includes determining a scaling factor that is voxel-dependent, and applying the voxel-dependent scaling factor to a gradient of an objective function to reconstruct the image.

Abstract: Methods provided for forward and back-projection, which are referred to as separable footprint (SF) projectors: exemplified by the SF-TR and SF-TT projectors. These methods approximate the voxel footprint functions as 2D separable functions. Because of the separability of these footprint functions, calculating their integrals over a detector cell is greatly simplified and can be implemented efficiently. In some embodiments, the SF-TR projector uses trapezoid functions in the transaxial direction and rectangular functions in the axial direction. In some embodiments, the SF-TT projector uses trapezoid functions in both the axial and transaxial directions. Simulations and experiments showed that both SF projector methods are more accurate than conventional distance-driven (DD) projectors. Moreover, the SF-TT projector is more accurate than the SF-TR projector for rays associated with large cone angles.

Abstract: A method and system for controlling image reconstruction in an imaging system are provided. The method includes receiving scan data from an imaging system, and determining regularization parameters for a plurality of portions of an image for reconstructing the image based on the received scan data, wherein the regularization parameters vary for the plurality of portions of the image.

Abstract: A method for statistically reconstructing images from a plurality of transmission measurements having energy diversity and image reconstructor apparatus utilizing the method are provided. A statistical (maximum-likelihood) method for dual-energy X-ray CT accommodates a wide variety of potential system configurations and measurement noise models. Regularized methods (such as penalized-likelihood or Bayesian estimations) are straightforward extensions. One version of the algorithm monotonically decreases the negative log-likelihood cost function each iteration. An ordered-subsets variation of the algorithm provides a fast and practical version. The method and apparatus provide material characterization and quantitatively accurate CT values in a variety of applications. The method and apparatus provide improved noise/dose properties.

Abstract: A method for statistically reconstructing images from a plurality of transmission measurements having energy diversity and image reconstructor apparatus utilizing the method are provided. A statistical (maximum-likelihood) method for dual-energy X-ray CT accommodates a wide variety of potential system configurations and measurement noise models. Regularized methods (such as penalized-likelihood or Bayesian estimations) are straightforward extensions. One version of the algorithm monotonically decreases the negative log-likelihood cost function each iteration. An ordered-subsets variation of the algorithm provides a fast and practical version. The method and apparatus provide material characterization and quantitatively accurate CT values in a variety of applications. The method and apparatus provide improved noise/dose properties.

Abstract: A method for statistically reconstructing an X-ray computed tomography image produced by a single X-ray CT scan having a polyenergetic source spectrum and an image reconstructor which utilize a convergent statistical algorithm which explicitly accounts for the polyenergetic source spectrum are provided. First and second related statistical iterative methods for CT reconstruction based on a Poisson statistical model are described. Both methods are accelerated by the use of ordered subsets, which replace sums over the angular index of a sinogram with a series of sums over angular subsets of the sinogram. The first method is generalized to model the more realistic case of polyenergetic computed tomography (CT). The second method eliminates beam hardening artifacts seen when filtered back projection (FBP) is used without post-processing correction. The methods are superior to FBP reconstruction in terms of noise reduction.