Abstract: A method is provided. The method includes acquiring a first dataset at a first energy spectrum and a second dataset at a second energy spectrum. The method also includes extracting a metal artifact correction signal using the first dataset and the second dataset or using a first reconstructed image and a second reconstructed image generated respectively from the first and the second datasets. The method further includes performing metal artifact correction on the first reconstructed image using the metal artifact correction signal to generate a first corrected image.

Abstract: A method for reconstructing an image of an object that includes a plurality of image elements. The method includes accessing image data associated with a plurality of image elements, and reconstructing an image of the object by optimizing an objective function, where the objective function is optimized by iteratively solving a nested sequence of approximate optimization problems. The algorithm is composed of nested iterative loops, in which an inner loop iteratively optimizes an objective function approximating the outer loop objective function, and an outer loop that utilizes the solution of the inner loop to optimize the original objective function.

Abstract: A method is provided. The method includes acquiring a first dataset at a first energy spectrum and a second dataset at a second energy spectrum. The method also includes extracting a metal artifact correction signal using the first dataset and the second dataset or using a first reconstructed image and a second reconstructed image generated respectively from the first and the second datasets. The method further includes performing metal artifact correction on the first reconstructed image using the metal artifact correction signal to generate a first corrected image.

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: A framework for an iterative reconstruction algorithm is described which combines two or more of an ordered subset method, a preconditioner method, and a nested loop method. In one type of implementation a nested loop (NL) structure is employed where the inner loop sub-problems are solved using ordered subset (OS) methods. The inner loop may be solved using OS and a preconditioner method. In other implementations, the inner loop problems are created by augmented Lagrangian methods and then solved using OS method.

Abstract: The use of the channelized preconditioners in iterative reconstruction is disclosed. In certain embodiments, different channels correspond to different frequency sub-bands and the output of the different channels can be combined to update an image estimate used in the iterative reconstruction process. While individual channels may be relatively simple, the combined channels can represent complex spatial variant operations. The use of channelized preconditioners allows empirical adjustment of individual channels.

Abstract: A method is provided. The method includes acquiring a first dataset at a first energy spectrum and a second dataset at a second energy spectrum. The method also includes extracting a metal artifact correction signal using the first dataset and the second dataset or using a first reconstructed image and a second reconstructed image generated respectively from the first and the second datasets. The method further includes performing metal artifact correction on the first reconstructed image using the metal artifact correction signal to generate a first corrected image.

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: An imaging system includes a rotatable gantry for receiving an object to be scanned, a generator configured to energize an x-ray source to generate x-rays, a detector positioned to receive the x-rays that pass through the object, and a computer. The computer is programmed to obtain knowledge of a metal within the object, scan the object using system scanning parameters, reconstruct an image of the object using a reconstruction algorithm, and automatically select at least one of the system scanning parameters and the reconstruction algorithm based on the obtained knowledge.

Abstract: Nuclear image data generated by a multimodal imaging device, such as a combined position emission tomography (PET)/magnetic resonance (MR) scanner (12, 14), is attenuation-corrected with a combined patient-specific attenuation correction (AC) map and an AC map template (70) for an MR coil (72) that is present in both the nuclear and MR scanning procedures. A template library (46) contains templates for each of a plurality of MR coils and other accessories. Each template is generated on one of two manners. The coil may be imaged inside the PET scanner 14 with the transmission source 16 (e.g., Ge-68 or Cs-137). A transmission image 48 is reconstructed using the known algorithms and may be used as the AC template directly. Alternatively, the template can be generated by creating a global histogram of the transmission image and identifying segments of the coil or other accessory. An average linear attenuation coefficient (LAC) value is determined from the distribution of the histogram.

Abstract: A tomographic system includes a gantry having an opening for receiving an object to be scanned, a radiation source, a detector positioned to receive radiation from the source that passes through the object, and a computer. The computer is programmed to acquire a plurality of projection datasets of the object, define a temporal subset of projection datasets from the plurality of projection datasets, reconstruct a working image of the object using the plurality of projection datasets, identify a region of motion in the working image, and minimize motion artifacts in the region of motion in the working image using the temporal subset of projection datasets.

Abstract: A method is provided. The method includes acquiring a first dataset at a first energy spectrum and a second dataset at a second energy spectrum. The method also includes extracting a metal artifact correction signal using the first dataset and the second dataset or using a first reconstructed image and a second reconstructed image generated respectively from the first and the second datasets. The method further includes performing metal artifact correction on the first reconstructed image using the metal artifact correction signal to generate a first corrected image.

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: A method for reconstructing an image of an object that includes a plurality of image elements. The method includes accessing image data associated with a plurality of image elements, and reconstructing an image of the object by optimizing an objective function, where the objective function is optimized by iteratively solving a nested sequence of approximate optimization problems. The algorithm is composed of nested iterative loops, in which an inner loop iteratively optimizes an objective function approximating the outer loop objective function, and an outer loop that utilizes the solution of the inner loop to optimize the original objective function.

Abstract: Nuclear image data generated by a multimodal imaging device, such as a combined position emission tomography (PET)/magnetic resonance (MR) scanner (12, 14), is attenuation-corrected with a combined patient-specific attenuation correction (AC) map and an AC map template (70) for an MR coil (72) that is present in both the nuclear and MR scanning procedures. template library (46) contains templates for each of a plurality of MR coils and other accessories. Each template is generated on one of two manners. The coil may be imaged inside the PET scanner 14 with the transmission source 16 (e.g., Ge-68 or Cs-137). A transmission image 48 is reconstructed using the known algorithms and may be used as the AC template directly. Alternatively, the template can be generated by creating a global histogram of the transmission image and identifying segments of the coil or other accessory. An average linear attenuation coefficient (LAC) value is determined from the distribution of the histogram.

Abstract: A tomographic system includes a gantry having an opening for receiving an object to be scanned, a radiation source, a detector positioned to receive radiation from the source that passes through the object, and a computer. The computer is programmed to acquire a plurality of projection datasets of the object, define a temporal subset of projection datasets from the plurality of projection datasets, reconstruct a working image of the object using the plurality of projection datasets, identify a region of motion in the working image, and minimize motion artifacts in the region of motion in the working image using the temporal subset of projection datasets.