Keywords: AI/ML Image Reconstruction, AI/ML Image Reconstruction
Motivation: Simultaneous Multi-Slice (SMS) reconstruction achieves slice separation by single-band calibration data or coil sensitivity maps through pre-scanning, resulting in SMS inefficiency.
Goal(s): Achieve real-time and robust contour acquisition through the depth camera.
Proposed a SMS reconstruction method via deep learning with auxiliary depth camera guidance.
Approach: We obtain the contour by placing the depth camera, locating phantom, and fixed markers within the MRI. We propose a Mamba-based network based on the auxiliary depth camera guidance to achieve faithful SMS reconstruction.
Results: The contour captured by the depth camera demonstrates effectiveness with less time-consuming and more robust, and the proposed Dep2SMS achieves outstanding reconstruction.
Impact: We novelty introduce the depth camera into the MRI system to capture contour to assist SMS reconstruction.
We utilize the Mamba-based framework with intra-patch convolution and linear-complexity long-range attention for SMS reconstruction to capture fine structural and global texture features.
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