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A deep unrolled neural network for real-time MRI-guided brain intervention.


ABSTRACT: Accurate navigation and targeting are critical for neurological interventions including biopsy and deep brain stimulation. Real-time image guidance further improves surgical planning and MRI is ideally suited for both pre- and intra-operative imaging. However, balancing spatial and temporal resolution is a major challenge for real-time interventional MRI (i-MRI). Here, we proposed a deep unrolled neural network, dubbed as LSFP-Net, for real-time i-MRI reconstruction. By integrating LSFP-Net and a custom-designed, MR-compatible interventional device into a 3 T MRI scanner, a real-time MRI-guided brain intervention system is proposed. The performance of the system was evaluated using phantom and cadaver studies. 2D/3D real-time i-MRI was achieved with temporal resolutions of 80/732.8 ms, latencies of 0.4/3.66 s including data communication, processing and reconstruction time, and in-plane spatial resolution of 1 × 1 mm2. The results demonstrated that the proposed method enables real-time monitoring of the remote-controlled brain intervention, and showed the potential to be readily integrated into diagnostic scanners for image-guided neurosurgery.

SUBMITTER: He Z 

PROVIDER: S-EPMC10716161 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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A deep unrolled neural network for real-time MRI-guided brain intervention.

He Zhao Z   Zhu Ya-Nan YN   Chen Yu Y   Chen Yi Y   He Yuchen Y   Sun Yuhao Y   Wang Tao T   Zhang Chengcheng C   Sun Bomin B   Yan Fuhua F   Zhang Xiaoqun X   Sun Qing-Fang QF   Yang Guang-Zhong GZ   Feng Yuan Y  

Nature communications 20231212 1


Accurate navigation and targeting are critical for neurological interventions including biopsy and deep brain stimulation. Real-time image guidance further improves surgical planning and MRI is ideally suited for both pre- and intra-operative imaging. However, balancing spatial and temporal resolution is a major challenge for real-time interventional MRI (i-MRI). Here, we proposed a deep unrolled neural network, dubbed as LSFP-Net, for real-time i-MRI reconstruction. By integrating LSFP-Net and  ...[more]

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