Abstract: Described is an approach for tracking 3D organ motion in real-time using magnetic resonance imaging (MRI). The approach may include offline learning, which may acquire signature and 3D imaging data over multiple respiratory cycles to create a database of high-resolution 3D motion states. The approach may further include online matching, which may acquire signature data only in real-time (latency less than 0.2 seconds). From a motion state and motion signature database, the 3D motion state whose signature best (or sufficiently) matches the newly-acquired signature data may be selected. Real-time 3D motion tracking may be accomplished by performing time-consuming acquisition and reconstruction work in an offline learning phase, leaving just signature acquisition and correlation analysis in an online matching step, minimizing or otherwise reducing latency. The approach may be used to adapt radiotherapy procedures based on tumor motion using a magnetic resonance linear accelerator (MR-Linac) system.

Abstract: Systems and methods are provided for predictive volumetric and structural evaluation of petroleum product containers. The system includes a computing device in communication with data input devices and implementation tools including calibration devices for measuring tank volume among other physical parameters bearing on tank volume. The computing device receives sets of historical physical parameter data for a plurality of tanks and, using machine learning (ML), generates predictive ML models for estimating volumetric parameters of tanks. The predictive model is applied by the system to historical and current data values to estimate current volumetric parameters for a given tank and, based on the results, the system performs or coordinates further operations for the given tank using an implementation tool. The further opera ions can include inventory management, physical calibration, maintenance and inspection as well as system evaluation and control operations.

Abstract: Described is an approach for tracking 3D organ motion in real-time using magnetic resonance imaging (MRI). The approach may include offline learning, which may acquire signature and 3D imaging data over multiple respiratory cycles to create a database of high-resolution 3D motion states. The approach may further include online matching, which may acquire signature data only in real-time (latency less than 0.2 seconds). From a motion state and motion signature database, the 3D motion state whose signature best (or sufficiently) matches the newly-acquired signature data may be selected. Real-time 3D motion tracking may be accomplished by performing time-consuming acquisition and reconstruction work in an offline learning phase, leaving just signature acquisition and correlation analysis in an online matching step, minimizing or otherwise reducing latency. The approach may be used to adapt radiotherapy procedures based on tumor motion using a magnetic resonance linear accelerator (MR-Linac) system.

Abstract: Exemplary method, system and computer-accessible medium can be provided which facilitates an acquisition of radial data, which can be continuous, with an exemplary golden-angle procedure and reconstruction with arbitrary temporal resolution at arbitrary time points. According to such exemplary embodiment, such procedure can be performed with a combination of compressed sensing and parallel imaging to offer a significant improvement, for example in the reconstruction of highly undersampled data. It is also possible to provide an exemplary procedure for highly-accelerated dynamic magnetic resonance imaging using Golden-Angle radial sampling and multicoil compressed sensing reconstruction, called Golden-angle Radial Sparse Parallel MRI (GRASP).

Abstract: Exemplary method, system and computer-accessible medium can be provided which facilitates an acquisition of radial data, which can be continuous, with an exemplary golden-angle procedure and reconstruction with arbitrary temporal resolution at arbitrary time points. According to such exemplary embodiment, such procedure can be performed with a combination of compressed sensing and parallel imaging to offer a significant improvement, for example in the reconstruction of highly undersampled data. It is also possible to provide an exemplary procedure for highly-accelerated dynamic magnetic resonance imaging using Golden-Angle radial sampling and multicoil compressed sensing reconstruction, called Golden-angle Radial Sparse Parallel MRI (GRASP).

Abstract: An exemplary system, method and computer-accessible medium can be provided for generating an image(s) of a tissue(s) that can include, for example, receiving magnetic resonance imaging information regarding the tissue(s) based on a golden-angle radial sampling procedure, sorting and synchronizing the MRI information into at least two dimensions, and generating the image(s) of the tissue(s) based on the sorted and synchronized information. The tissue(s) include cardiac tissue and respiratory-affected tissue. The MRI information can include a motion of the cardiac tissue and a motion of the respiratory tissue.

Abstract: Exemplary system, method and computer-accessible medium for determining a difference(s) between two sets of subjects, can be provided. Using such exemplary system, method and computer-accessible medium, it is possible to receive first imaging information related to a first set of subjects of the two sets of the subjects, receive second imaging information related to a second set of subjects of the two sets of subjects, generate third information by performing a decomposition procedure(s) on the first imaging information and the second information, and determine the difference(s) based on the third information.

Abstract: Exemplary method, system and computer-accessible medium can be provided which facilitates an acquisition of radial data, which can be continuous, with an exemplary golden-angle procedure and reconstruction with arbitrary temporal resolution at arbitrary time points. According to such exemplary embodiment, such procedure can be performed with a combination of compressed sensing and parallel imaging to offer a significant improvement, for example in the reconstruction of highly undersampled data. It is also possible to provide an exemplary procedure for highly-accelerated dynamic magnetic resonance imaging using Golden-Angle radial sampling and multicoil compressed sensing reconstruction, called Golden-angle Radial Sparse Parallel MRI (GRASP).

Abstract: An imaging system for imaging a portion(s) of an anatomical structure can be provided. For example, an x-ray source first arrangement can provide x-ray radiation, and a multi-hole collimator second arrangement can be provided in a path of the x-ray radiation, and can be configured to undersample the radiation beam which can be forwarded to the portion(s) of the anatomical structure. A third hardware arrangement can be configured to receive a further x-ray radiation from the portion(s) that can be based on the undersampled x-ray radiation.

Abstract: An exemplary system, method and computer-accessible medium for generating a magnetic resonance (MR) image(s) and a positron emission tomography (PET) image(s) of a tissue(s) can be provided, which can include, for example, receiving information related to a combination of MR data and PET data as a single data set, separating the information into at least two dimensions, at least one first of the dimensions corresponding to the MR data and at least one second of the dimensions corresponding to the PET data, and generating the MR image(s) and the PET image(s) based on the separated information.

Abstract: Exemplary method, system and computer-accessible medium can be provided which facilitates an acquisition of radial data, which can be continuous, with an exemplary golden-angle procedure and reconstruction with arbitrary temporal resolution at arbitrary time points. According to such exemplary embodiment, such procedure can be performed with a combination of compressed sensing and parallel imaging to offer a significant improvement, for example in the reconstruction of highly undersampled data. It is also possible to provide an exemplary procedure for highly-accelerated dynamic magnetic resonance imaging using Golden-Angle radial sampling and multicoil compressed sensing reconstruction, called Golden-angle Radial Sparse Parallel MRI (GRASP).

Abstract: Exemplary system, method and computer-accessible medium for determining a difference(s) between two sets of subjects, can be provided. Using such exemplary system, method and computer-accessible medium, it is possible to receive first imaging information related to a first set of subjects of the two sets of the subjects, receive second imaging information related to a second set of subjects of the two sets of subjects, generate third information by performing a decomposition procedure(s) on the first imaging information and the second information, and determine the difference(s) based on the third information.

Abstract: An imaging system for imaging a portion(s) of an anatomical structure can be provided. For example, a source first arrangement can provide x-ray radiation, and a multi-hole collimator second arrangement can be provided in a path of the x-ray radiation, and can be configured to undersample the radiation beam which can be forwarded to the portion(s) of the anatomical structure. A third hardware arrangement can be configured to receive a further radiation from the portion(s) that can be based on the undersampled radiation.

Abstract: An exemplary system, method and computer-accessible medium can be provided for generating an image(s) of a tissue(s) that can include, for example, receiving magnetic resonance imaging information regarding the tissue(s) based on a golden-angle radial sampling procedure, sorting and synchronizing the MRI information into at least two dimensions, and generating the image(s) of the tissue(s) based on the sorted and synchronized information. The tissue(s) include cardiac tissue and respiratory-affected tissue. The MRI information can include a motion of the cardiac tissue and a motion of the respiratory tissue.

Abstract: An exemplary system, method and computer-accessible medium for generating a magnetic resonance (MR) image(s) and a positron emission tomography (PET) image(s) of a tissue(s) can be provided, which can include, for example, receiving information related to a combination of MR data and PET data as a single data set, separating the information into at least two dimensions, at least one first of the dimensions corresponding to the MR data and at least one second of the dimensions corresponding to the PET data, and generating the MR image(s) and the PET image(s) based on the separated information.

Abstract: Exemplary method, system and computer-accessible medium can be provided which facilitates an acquisition of radial data, which can be continuous, with an exemplary golden-angle procedure and reconstruction with arbitrary temporal resolution at arbitrary time points. According to such exemplary embodiment, such procedure can be performed with a combination of compressed sensing and parallel imaging to offer a significant improvement, for example in the reconstruction of highly undersampled data. It is also possible to provide an exemplary procedure for highly-accelerated dynamic magnetic resonance imaging using Golden-Angle radial sampling and multicoil compressed sensing reconstruction, called Golden-angle Radial Sparse Parallel MRI (GRASP).

Abstract: The present invention includes a method for parallel magnetic resonance imaging termed Superresolution Sensitivity Encoding (SURE-SENSE) and its application to functional and spectroscopic magnetic resonance imaging. SURE-SENSE acceleration is performed by acquiring only the central region of k-space instead of increasing the sampling distance over the complete k-space matrix and reconstruction is explicitly based on intra-voxel coil sensitivity variation. SURE-SENSE image reconstruction is formulated as a superresolution imaging problem where a collection of low resolution images acquired with multiple receiver coils are combined into a single image with higher spatial resolution using coil sensitivity maps acquired with high spatial resolution. The effective acceleration of conventional gradient encoding is given by the gain in spatial resolution Since SURE-SENSE is an ill-posed inverse problem, Tikhonov regularization is employed to control noise amplification.