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1.发明申请公开(公告)号：US20230082616A1
公开(公告)日：2023-03-16
申请号：US17988825
申请日：2022-11-17
发明人： Andrew J. WHEATON , Anuj SHARMA , Samir Dev SHARMA
IPC分类号： G06T11/00 , G01R33/565 , G01R33/48 , G01R33/56
摘要： An apparatus for incremental motion correction in medical imaging. The apparatus for motion correction in magnetic resonance imaging includes processing circuitry configured to estimate an intermediate image from a first section of k-space, the first section of the k-space corresponding to acquisition time points within a magnetic resonance scan of a subject, the corresponding acquisition time points within the magnetic resonance scan being associated with shots of the k-space determined to have minimal motion, estimate motion parameters of a second section of the k-space using the estimated intermediate image, combine data from the first section of the k-space with data from the second section of the k-space according to the estimated motion parameters, and reconstruct the combined data of the k-space to generate a final image.
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2.发明申请公开(公告)号：US20220172410A1
公开(公告)日：2022-06-02
申请号：US17110077
申请日：2020-12-02
发明人： Andrew J. WHEATON , Anuj SHARMA , Samir Dev SHARMA
IPC分类号： G06T11/00 , G01R33/565 , G01R33/56 , G01R33/48
摘要： An apparatus for incremental motion correction in medical imaging. The apparatus for motion correction in magnetic resonance imaging includes processing circuitry configured to estimate an intermediate image from a first section of k-space, the first section of the k-space corresponding to acquisition time points within a magnetic resonance scan of a subject, the corresponding acquisition time points within the magnetic resonance scan being associated with shots of the k-space determined to have minimal motion, estimate motion parameters of a second section of the k-space using the estimated intermediate image, combine data from the first section of the k-space with data from the second section of the k-space according to the estimated motion parameters, and reconstruct the combined data of the k-space to generate a final image.
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3.发明申请公开(公告)号：US20200278406A1
公开(公告)日：2020-09-03
申请号：US16290574
申请日：2019-03-01
发明人： Samir Dev SHARMA
IPC分类号： G01R33/48 , G01R33/485 , G01R33/561 , G01R33/565
摘要： A method and apparatuses are provided to perform chemical species separation in magnetic resonance (MR) imaging (MRI). At least three MR images corresponding respectively to different echo times are obtained and represent signals from multiple chemical species including a first species and a second species in a tissue. A plurality of dual-echo pairs is selected from the at least three MR images. For each pair, a set of dual-echo separated images including a B0 field map, a first image for the first species, and a second image for the second species is estimated. An initial set of combined images including at least one of: an initial combined B0 field map, first, and second image is generated by combining at least one of: two or more of the B0 field maps, two or more of the first images, and two or more of the second images.
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4.发明公开公开(公告)号：US20230284995A1
公开(公告)日：2023-09-14
申请号：US17690834
申请日：2022-03-09
发明人： Samir Dev SHARMA
CPC分类号： A61B6/5241 , A61B6/5258 , G06T7/0012 , G06T2207/10088
摘要： The present disclosure relates to a method and apparatus correcting a metal artifact in magnetic resonance imaging (MRI) data. The method and apparatus acquire plural slices along a slice direction of a scanned region associated with a body part, estimate a spatial extent of a signal dispersion of the acquired plural slices along the slice direction, and combine the signal of the acquired plural slices along the slice direction based on the estimated spatial extent of the signal dispersion to generate a reconstructed image of the scanned region. The method and apparatus may identify, from the acquired plural slices along the slice direction, a slice with a highest pixel intensity; and identify at least one neighboring slice neighboring the slice with the highest pixel intensity based on a 3D spatial dipole response function, wherein combining the signal of the acquired plural slices along the slice direction based on the estimated spatial extent of the signal dispersion comprises combining (a) the signal of the slice with the highest pixel intensity and (b) the signal of the at least one neighboring slice.
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公开(公告)号：US20240153164A1
公开(公告)日：2024-05-09
申请号：US18501336
申请日：2023-11-03
发明人： Mathews JACOB , Aniket PRAMANIK , Samir Dev SHARMA
IPC分类号： G06T11/00
CPC分类号： G06T11/006 , G06T2210/41 , G06T2211/441
摘要： An apparatus for reconstructing or filtering medical image data is provided. The apparatus includes processing circuitry to receive a first medical image data and meta-parameters related to the first medical image data; apply the received meta-parameters to inputs of a first trained machine-learning (ML) network, e.g., a multilayer perceptron, to obtain, from outputs of the first trained ML network, tuning parameters of a second ML network (e.g., a convolutional neural network) different from the first ML network; apply the received first medical image data to inputs of the second ML network, as tuned by the obtained tuning parameters output from the first ML network, to obtain, from outputs of the second ML network, second medical image data; and output the second medical image data. In one embodiment, the first medical image data is magnetic-resonance k-space data and the second medical data is a magnetic-resonance image.
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公开(公告)号：US20210315475A1
公开(公告)日：2021-10-14
申请号：US17313055
申请日：2021-05-06
摘要： An apparatus and method are provided to simultaneously provide good image quality and fast image reconstruction from magnetic resonance imaging (MRI) data by selecting an appropriate value for the regularization parameter used in compressed sensing (CS) image reconstruction. In CS reconstruction a high-resolution image can be reconstructed from randomized undersampled data by imposing sparsity in multi-scale transformation (e.g., wavelet) domain. Further, in the transformation domain, a threshold can be determined between signal and noise levels of the transform coefficients. A regularization parameter based on this threshold scales the regularization term, which imposes sparsity, relative to the data fidelity term in an objective function, thereby balancing the tradeoff between noise and smoothing.
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