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Abstract #2038

A Recurrent Neural Network Based Real-Time Reconstruction Method for MRI Navigation in Robot Assisted Intervention

Sijie Zhong1, Shaoping Huang1,2, Hao Chen1,2, Anzhu Gao2,3, Guang-Zhong Yang1,2, and Zhiyong Zhang1
1School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China, 2Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China, 3Department of Automation, Shanghai Jiao Tong University, Shanghai, China

Synopsis

Keywords: MR-Guided Interventions, Image Reconstruction

Motivation: MRI navigation for intervention requires higher imaging efficiency, and deep learning-based algorithms significantly reduce reconstruction time.

Goal(s): To develop a deep learning-based MRI reconstruction method suitable for interventional navigation tasks.

Approach: This study proposes an unfolded neural network to reconstruct radial sampling sequences, integrating the data consistency term with both parallel and serial network structures, and incorporating a data-sharing term at the beginning.

Results: Under limited computational resources, the proposed method demonstrates superior performance compared to the comparative methods on two tested datasets.

Impact: We propose a promising MRI reconstruction algorithm suitable for navigation scenarios, which will help advance our goals in MRI-guided surgeries.

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Keywords