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Abstract #0862

Robust Image Reconstruction using Multi-channel Spatial Nulling Maps: An Alternative to ESPIRiT?

Jiahao Hu1,2,3, Yi Zheyuan1,2,3, Yujiao Zhao1,2, Junhao Zhang1,2, Linfang Xiao1,2, Christopher Man1,2, Vick Lau1,2, Alex T. L. Leong1,2, Fei Chen3, and Ed X. Wu1,2
1Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong, Hong Kong, 2Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, Hong Kong, 3Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China

Synopsis

Keywords: Signal Representations, Parallel ImagingWe develop a novel parallel imaging reconstruction method by extracting null-subspace bases of calibration data/matrix to calculate image-domain spatial nulling maps that contain both coil sensitivity and finite image support information. Images are reconstructed by solving a nulling system formed by multi-channel spatial nulling maps without any masking-related procedure (i.e., in existing SENSE/ESPIRiT for minimizing noise propagation). We demonstrate this method with 2D brain, knee and cardiac data under various conditions, yielding results highly comparable to ESPIRiT with optimal manual masking. Our proposed hybrid-domain reconstruction method is efficient, and more robust than existing ESPIRiT for parallel imaging in practice.

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