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Abstract #4417

A Novel Hybrid Method for Gradient Nonlinearity (GNL) Correction for MRI- Linac system

Shanshan shan1, Mingyan Li1, Yaohui Wang2, Fangfang Tang1, Deming Wang1, Haiwei Chen1, Ewald Weber1, Rafael Franco1, Craig Freakley 1, Feng Liu1, and Stuart Crozier1

1The University of Queensland, Brisbane, Australia, 2South China University of Technology, Guangzhou, China

MRI-guided radiotherapy requires precise image geometric information to target a tumour without unnecessary radiation on healthy surrounding tissue. Due to the imperfections in the gradient system and engineering limitations, however, gradient non-linearity (GNL) inevitably occurs and causes image distortions if not properly accounted for. Here we propose a novel method to estimate the gradient field using stream function methods with a grid phantom. The estimated gradient field was then used for GNL distortion correction and image reconstruction. Initial simulations demonstrated that the image geometric distortion in a combined MRI and linear accelerator (MRI-Linac) system was effectively improved by the proposed method.

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