Chinese Academy of Sciences

State Grid Corporation of China

China Electric Power Research Institute Company Limited

Zechen Wei

Xin Yang

Jie Tian

Hui Hui

Wei Wang

Kun Wu

Chen Bo Li

Lixin Li

Wei Han

Shiguang Li

Tao Zhu

Tianjiao Pu

Yijun Yu

Shixiong Fan

Liwen Zhang

Ting Yu

Huiling Peng

Xingwei Liu

Xinjing Wu

Jiatong Du

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.

System for reconstructing magnetic particle image based on pre-trained model

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.

System for reconstructing magnetic particle image based on adaptive optimization of regularization terms

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.

Method and system for reconstructing magnetic particle distribution model based on time-frequency spectrum enhancement

A method and an apparatus for determining the distributed power supply capacity to be accessed by a feed line of a power distribution network, and a storage medium, the method comprising: determining feed line loss on the basis of load information of power distribution network feed line access nodes and circuit parameters; on the basis of the feed line loss, determining three-phase voltage change values of the feed line circuit; using a single phase having the greatest voltage change amongst the voltage change values, determining a maximum active power for distributed power supply access under voltage constraints; comparing the current of the feed line corresponding to the maximum active power with a circuit current limit, and determining the distributed power supply capacity to be accessed by the feed line; the apparatus comprises a feed line information collection unit, a voltage drop unit, a quantitative calculation unit, and a results analysis unit. The present method can be used for dispatching operation control of a distributed power supply in a power grid, and can ensure safe access to the distributed power supply and safe operation of the power grid, improving the access capacity of the power distribution network to the distributed power supply.

Method, apparatus and storage medium for determining distributed power supply access capacity

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Beijing, China

Zechen Wei