Abstract: Techniques regarding the management of computational resources based on clinical priority associated with one or more computing tasks are provided. For example, one or more embodiments described herein can regard a system comprising a memory that can store computer-executable components. The system can also comprise a processor, operably coupled to the memory, that executes the computer-executable components stored in the memory. The computer-executable components can include a prioritization component that can prioritize computer applications based on a clinical priority of tasks performed by the computer applications. The clinical priority can characterize a time sensitivity of the tasks. The computer-executable components can also include a resource pool component that can divide computational resources across a plurality of resource pools and can assign the computer applications to the plurality of resource pools based on the clinical priority.

Abstract: Techniques regarding the management of computational resources based on clinical priority associated with one or more computing tasks are provided. For example, one or more embodiments described herein can regard a system comprising a memory that can store computer-executable components. The system can also comprise a processor, operably coupled to the memory, that executes the computer-executable components stored in the memory. The computer-executable components can include a prioritization component that can prioritize computer applications based on a clinical priority of tasks performed by the computer applications. The clinical priority can characterize a time sensitivity of the tasks. The computer-executable components can also include a resource pool component that can divide computational resources across a plurality of resource pools and can assign the computer applications to the plurality of resource pools based on the clinical priority.

Abstract: Methods and systems are provided for high-resolution computed tomography imaging. In one embodiment, a method comprises detecting, with a detector array comprising a plurality of individual detectors each configured with a first number of energy bins, photons generated by an x-ray source and attenuated by a subject to be imaged, generating a first dataset, for a virtual detector array comprising a combination of individual detectors and macro-detectors, by selectively aggregating a subset of the individual detectors into the macro-detectors with a second number of energy bins, generating a second dataset, for an augmented detector array comprising the plurality of individual detectors each configured with the second number of energy bins, by up-sampling the first dataset, and reconstructing an image of the subject from the second dataset. In this way, high-resolution detector arrays can acquire minimal data while maintaining a high image resolution and spectral resolution.

Abstract: Methods and systems are provided for high-resolution computed tomography imaging. In one embodiment, a method comprises detecting, with a detector array comprising a plurality of individual detectors each configured with a first number of energy bins, photons generated by an x-ray source and attenuated by a subject to be imaged, generating a first dataset, for a virtual detector array comprising a combination of individual detectors and macro-detectors, by selectively aggregating a subset of the individual detectors into the macro-detectors with a second number of energy bins, generating a second dataset, for an augmented detector array comprising the plurality of individual detectors each configured with the second number of energy bins, by up-sampling the first dataset, and reconstructing an image of the subject from the second dataset. In this way, high-resolution detector arrays can acquire minimal data while maintaining a high image resolution and spectral resolution.

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: 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: 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 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 and apparatus for processing raw image data to create processed images. Raw image data is acquired. The raw image data is decomposed by a data decomposer into N subsets of raw image data. The number N is based on a number of available image generation processors. The N subsets of raw image data are processed by at least one image generation processor to create processed image data. If more than one image generation processor is available, the image generation processors perform image processing on the raw image data in parallel with respect to each other.

Abstract: A method and apparatus for processing raw image data to create processed images. Raw image data is acquired. The raw image data is decomposed by a data decomposer into N subsets of raw image data. The number N is based on a number of available image generation processors. The N subsets of raw image data are processed by at least one image generation processor to create processed image data. If more than one image generation processor is available, the image generation processors perform image processing on the raw image data in parallel with respect to each other.

Abstract: A method and apparatus for processing raw image data to create processed images. Raw image data is acquired. The raw image data is decomposed by a data decomposer into N subsets of raw image data. The number N is based on a number of available image generation processors. The N subsets of raw image data are processed by at least one image generation processor to create processed image data. If more than one image generation processor is available, the image generation processors perform image processing on the raw image data in parallel with respect to each other.

Abstract: An adaptive CT data acquisition system and technique is presented whereby radiation emitted for CT data acquisition is dynamically controlled to limit exposure to those detectors of a CT detector assembly that may be particularly susceptible to saturation during a given data acquisition. The data acquisition technique recognizes that for a given subject size and position that pre-subject filtering and collimating of a radiation beam may be insufficient to completely prevent detector saturation. Therefore, the present invention includes implementation of a number of CT data correction techniques for correcting otherwise unusable data of a saturated CT detector. These data correction techniques include a nearest neighbor correction, off-centered phantom correction, off-centered synthetic data correction, scout data correction, planar radiogram correction, and a number of others.

Abstract: An adaptive CT data acquisition system and technique is presented whereby radiation emitted for CT data acquisition is dynamically controlled to limit exposure to those detectors of a CT detector assembly that may be particularly susceptible to saturation during a given data acquisition. The data acquisition technique recognizes that for a given subject size and position that pre-subject filtering and collimating of a radiation beam may be insufficient to completely prevent detector saturation. Therefore, the present invention includes implementation of a number of CT data correction techniques for correcting otherwise unusable data of a saturated CT detector. These data correction techniques include a nearest neighbor correction, off-centered phantom correction, off-centered synthetic data correction, scout data correction, planar radiogram correction, and a number of others.

Abstract: An adaptive CT data acquisition system and technique is presented whereby radiation emitted for CT data acquisition is dynamically controlled to limit exposure to those detectors of a CT detector assembly that may be particularly susceptible to saturation during a given data acquisition. The data acquisition technique recognizes that for a given subject size and position that pre-subject filtering and collimating of a radiation beam may be insufficient to completely prevent detector saturation. Therefore, the present invention includes implementation of a number of CT data correction techniques for correcting otherwise unusable data of a saturated CT detector. These data correction techniques include a nearest neighbor correction, off-centered phantom correction, off-centered synthetic data correction, scout data correction, planar radiogram correction, and a number of others.

Abstract: An adaptive CT data acquisition system and technique is presented whereby radiation emitted for CT data acquisition is dynamically controlled to limit exposure to those detectors of a CT detector assembly that may be particularly susceptible to saturation during a given data acquisition. The data acquisition technique recognizes that for a given subject size and position that pre-subject filtering and collimating of a radiation beam may be insufficient to completely prevent detector saturation. Therefore, the present invention includes implementation of a number of CT data correction techniques for correcting otherwise unusable data of a saturated CT detector. These data correction techniques include a nearest neighbor correction, off-centered phantom correction, off-centered synthetic data correction, scout data correction, planar radiogram correction, and a number of others.

Abstract: A method and apparatus for processing raw image data to create processed images. Raw image data is acquired. The raw image data is decomposed by a data decomposer into N subsets of raw image data. The number N is based on a number of available image generation processors. The N subsets of raw image data are processed by at least one image generation processor to create processed image data. If more than one image generation processor is available, the image generation processors perform image processing on the raw image data in parallel with respect to each other.

Abstract: An adaptive CT data acquisition system and technique is presented whereby radiation emitted for CT data acquisition is dynamically controlled to limit exposure to those detectors of a CT detector assembly that may be particularly susceptible to saturation during a given data acquisition. The data acquisition technique recognizes that for a given subject size and position that pre-subject filtering and collimating of a radiation beam may be insufficient to completely prevent detector saturation. Therefore, the present invention includes implementation of a number of CT data correction techniques for correcting otherwise unusable data of a saturated CT detector. These data correction techniques include a nearest neighbor correction, off-centered phantom correction, off-centered synthetic data correction, scout data correction, planar radiogram correction, and a number of others.

Abstract: An imaging system and method for determining sensor position and orientation with respect to an object having a known three dimensional structure is disclosed. The sensor acquires an image of the known structure. Position and orientation of the sensor is determined by processing the image with formulas corresponding to the known structure. One embodiment of the present invention comprises an ultrasound training system and method for determining the position and orientation of an ultrasound probe with respect to a known three dimensional structure embodied in an ultrasound phantom. The ultrasound probe acquires a cross sectional or partial volume image of the ultrasound phantom. The image is processed to obtain a number of geometrical image parameters. Position and orientation of the ultrasound probe are calculated from the image parameters using formulas based on the known three dimensional structure. The determination of probe position and orientation may be enhanced using image de-correlation techniques.

Abstract: An ultrasound system comprises a front end subsystem and a back end subsystem. The back end subsystem processes data samples representative of the echo signals from the front end subsystem. The back end subsystem includes at least one microprocessor with registers that simultaneously store at least two data samples. The microprocessor performs parallel common arithmetic or logic instructions upon at least two ultrasound data samples in one register. The microprocessor may be configured to scan convert polar data samples to Cartesian pixel values. During scan conversion, one register simultaneously stores multiple polar data samples and another register simultaneously stores coefficients associated with the polar data samples. The microprocessor multiplies corresponding data samples and coefficients, and sums the product of the parallel multiplication operations in order to produce a Cartesian data sample associated with a pixel to be displayed on an image arranged in a Cartesian coordinate pattern.

Abstract: A method and apparatus for providing a virtual volumetric ultrasound phantom to construct an ultrasound training system from any ultrasound system (hereafter "the ultrasound training system").The ultrasound system and method retrieve and display previously stored ultrasound data to simulate an ultrasound scanning session. A real ultrasound system acquires an image of an ultrasound phantom. The ultrasound image comprises ultrasound echo data for an image/scan plane representing a cross-section or partial volume of the ultrasound phantom. The ultrasound image is analyzed to identify image attributes that are unique for each image/scan plane. A portion of the previously stored data that corresponds to the image attributes is retrieved and displayed. In one embodiment, actual position and orientation of the acquired image/scan plane with respect to a known structure within the ultrasound phantom are determined by processing the image/scan plane to obtain a number of geometrical image parameters.