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1.发明授权公开(公告)号：US12136145B2
公开(公告)日：2024-11-05
申请号：US17811738
申请日：2022-07-11
IPC: G06T11/00 , A61B5/00 , A61B5/0515
Abstract: The present disclosure includes: transforming a time-domain voltage signal collected by an MPI system device to a frequency domain; calculating a square root of a square sum of a real part and an imaginary part at each frequency point of a frequency domain signal; arranging acquired amplitudes in a descending order, and acquiring a screening threshold by an amplitude ratio method; screening an amplitude through the screening threshold and constructing frequency domain signal data; acquiring a row vector of a system matrix corresponding to each frequency point of the data, so as to construct an update system matrix; and solving, based on the frequency domain signal array and the update system matrix, an inverse problem in a form of a least square based on an L2 constraint to obtain a three-dimensional magnetic particle concentration distribution result, so as to achieve a fast reconstruction of the MPI system.
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2.发明授权公开(公告)号：US11771336B2
公开(公告)日：2023-10-03
申请号：US17811235
申请日：2022-07-07
Inventor： Jie Tian , Yanjun Liu , Hui Hui , Lin Yin , Xin Feng
IPC: A61B5/0515 , G01R33/54
CPC classification number: A61B5/0515 , G01R33/54
Abstract: The present disclosure belongs to a field of biomedical imaging technology, and in particularly to a non-uniform excitation field-based method and system for performing a magnetic nanoparticle imaging. The present disclosure includes: separating the non-uniform excitation field into independent space and current time functions by a spatialtemporal separation method; calculating a normalized signal peak through the current time function; constructing a reconstruction mathematical model based on the normalized signal peak and an imaging subunit volume; and quantitatively reconstructing a spatial distribution of a nanoparticle by combining the normalized signal peak, a non-uniform spatial function of the excitation field and the reconstruction mathematical model, so as to achieve the magnetic nanoparticle imaging of a to-be-reconstructed object.
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3.发明申请公开(公告)号：US20230027988A1
公开(公告)日：2023-01-26
申请号：US17811738
申请日：2022-07-11
IPC: G06T11/00 , A61B5/0515 , A61B5/00
Abstract: The present disclosure includes: transforming a time-domain voltage signal collected by an MPI system device to a frequency domain; calculating a square root of a square sum of a real part and an imaginary part at each frequency point of a frequency domain signal; arranging acquired amplitudes in a descending order, and acquiring a screening threshold by an amplitude ratio method; screening an amplitude through the screening threshold and constructing frequency domain signal data; acquiring a row vector of a system matrix corresponding to each frequency point of the data, so as to construct an update system matrix; and solving, based on the frequency domain signal array and the update system matrix, an inverse problem in a form of a least square based on an L2 constraint to obtain a three-dimensional magnetic particle concentration distribution result, so as to achieve a fast reconstruction of the MPI system.
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Patent Agency Ranking
公开(公告)号：US11816767B1
公开(公告)日：2023-11-14
申请号：US18218115
申请日：2023-07-05
Inventor： Jie Tian , Zechen Wei , Hui Hui , Xin Yang , Huiling Peng
IPC: G06K9/00 , G06T11/00 , G06T5/00 , G06T5/10 , A61B5/0515
CPC classification number: G06T11/006 , A61B5/0515 , G06T5/002 , G06T5/10 , G06T2207/10072 , G06T2207/20081 , G06T2207/20084
Abstract: A method and system for reconstructing a magnetic particle distribution model based on time-frequency spectrum enhancement are provided. The method includes: scanning, by a magnetic particle imaging (MPI) device, a scan target to acquire a one-dimensional time-domain signal of the scan target; performing short-time Fourier transform to acquire a time-frequency spectrum; acquiring, by a deep neural network (DNN) fused with a self-attention mechanism, a denoised time-frequency spectrum; acquiring a high-quality magnetic particle time-domain signal; and reconstructing a magnetic particle distribution model. The method learns global and local information in the time-frequency spectrum through the DNN fused with the self-attention mechanism, thereby learning a relationship between different harmonics to distinguish between a particle signal and a noise signal. The method combines the global and local information to complete denoising of the time-frequency spectrum, thereby acquiring the high-quality magnetic particle time-domain signal.
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5.发明申请公开(公告)号：US20230094291A1
公开(公告)日：2023-03-30
申请号：US17811235
申请日：2022-07-07
Inventor： Jie Tian , Yanjun Liu , Hui Hui , Lin Yin , Xin Feng
IPC: A61B5/0515 , G01R33/54
Abstract: The present disclosure belongs to a field of biomedical imaging technology, and in particularly to a non-uniform excitation field-based method and system for performing a magnetic nanoparticle imaging. The present disclosure includes: separating the non-uniform excitation field into independent space and current time functions by a spatialtemporal separation method; calculating a normalized signal peak through the current time function; constructing a reconstruction mathematical model based on the normalized signal peak and an imaging subunit volume; and quantitatively reconstructing a spatial distribution of a nanoparticle by combining the normalized signal peak, a non-uniform spatial function of the excitation field and the reconstruction mathematical model, so as to achieve the magnetic nanoparticle imaging of a to-be-reconstructed object.
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公开(公告)号：US12136146B1
公开(公告)日：2024-11-05
申请号：US18752758
申请日：2024-06-24
Inventor： Jie Tian , Zechen Wei , Hui Hui , Xin Yang
IPC: G06T11/00 , A61B5/0515 , G06T3/4046
Abstract: A system for reconstructing a magnetic particle image based on a pre-trained model aims to address the influence by point spread function and reduce the computational and time costs, which results in low reconstruction accuracy, or high acquisition time and computational costs for high-precision images. The system is implemented by: generating a simulation system matrix; pre-training a pre-constructed neural network model, and fine-tuning a pre-trained neural network model by performing a downstream task; and inputting real data corresponding to the downstream task into the pre-trained neural network model after fine-tuning, thereby playing an auxiliary role to acquire a high-quality reconstructed MPI image. The system fits the relationship between different harmonics, which helps enhance frequency-domain information. The system has certain universality and can be generalized to a plurality of downstream tasks related to MPI image reconstruction, thereby acquiring high-quality reconstructed images through simple model fine-tuning.
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公开(公告)号：US12117508B1
公开(公告)日：2024-10-15
申请号：US18744685
申请日：2024-06-16
Inventor： Jie Tian , Zechen Wei , Hui Hui , Liwen Zhang , Xin Yang , Tao Zhu
IPC: G01R33/12 , A61B5/0515 , G06T11/00
CPC classification number: G01R33/1276 , A61B5/0515 , G06T11/006 , G06T2211/441
Abstract: A system for reconstructing a magnetic particle image based on adaptive optimization of regularization terms includes: a MPI device for scanning an imaging object to acquire a voltage response signal; a signal processor for constructing a system matrix; and a control processor for reconstructing the magnetic particle image based on an arbitrarily selected regularization term, inputting the reconstructed magnetic particle image to a regularization-term adaptive optimization neural network model for enhancement processing, taking the enhanced magnetic particle image as a first image, and calculating a loss value between the first image and an initial image to acquire a final reconstructed magnetic particle image. The system adopts a neural network model-based automatic learning approach, instead of the approach of manually selecting regularization terms and adjusting parameters, to improve the reconstruction efficiency and quality of the magnetic particle image.
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8.发明授权公开(公告)号：US10939845B2
公开(公告)日：2021-03-09
申请号：US16907334
申请日：2020-06-22
Inventor： Jie Tian , Peng Zhang , Hui Hui , Kun Wang , Xin Yang
IPC: A61B5/0515 , A61B5/00
Abstract: A FFL-based magnetic particle imaging three-dimensional reconstruction method includes: acquiring current signal data of an induction coil during FFL-based three-dimensional scanning process of a scanned object; based on the current signal data, performing deconvolution through a preset kernel function to acquire a two-dimensional image data set, wherein the kernel function is a step function with L2 regularized constraint; based on the two-dimensional image data set, acquiring an initial three-dimensional image by using a Wiener filtering deconvolution algorithm; and based on the initial three-dimensional image, performing deconvolution through a Langevin function, and acquiring a final three-dimensional image by Radon transformation. A FFL-based magnetic particle imaging three-dimensional reconstruction system includes a magnet group, an induction coil, an imaging bed, and a control and imaging device, wherein, a magnetic particle imaging method in the control and imaging device is the FFL-based magnetic particle imaging three-dimensional reconstruction method.
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