Model-based distortion correction for Magnetic Resonance Echo Planar Imaging

Sudhanya Chatterjee, Florian Wiesinger, Rajagopalan Sundaresan, Patricia Lan, Dattesh D. Shanbhag, Arnaud Guidon

Keywords: EPI, distortion correction, model based, field inhomogeneities, unrolled.

Abstract: Echo planar imaging (EPI) enables rapid magnetic resonance (MR) imaging and is widely used in applications such as diffusion-weighted imaging (DWI) and functional MRI (fMRI). However, EPI is highly susceptible to geometric distortion artifacts, which degrade image quality and hinder accurate diagnosis. In this work, we propose a reconstruction framework that leverages AI-learned priors within a model-based approach to correct EPI distortions. The method was evaluated on multiple in-vivo MRI datasets, including phantom, brain, and prostate diffusion-weighted imaging. Experimental results demonstrate the effectiveness of the proposed technique in mitigating distortion artifacts, thereby improving the reliability of EPI-based imaging.

Primary Subject Area: Image Acquisition and Reconstruction

Secondary Subject Area: Safe and Trustworthy Learning-assisted Solutions for Medical Imaging

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Originality Policy: Yes

Single-blind & Not Under Review Elsewhere: Yes

LLM Policy: Yes

Submission Number: 278