Meeting Banner
Abstract #0956

Gibbs-ringing Removal through Anti-aliased Deep Priors

Jaeuk Yi1, Chuanjiang Cui1, Kyu-Jin Jung1, and Dong-Hyun Kim1
1Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea, Republic of


Inspired by recent usage of Deep Image Prior (DIP) in the field of MRI that utilizes a powerful low-level image prior from a neural network architecture itself without any training dataset, we conduct k-space extrapolation using the deep prior for Gibbs-ringing removal in order to build general Gibbs-ringing correction algorithm without dependency on the dataset. We further improved the existing deep prior with the addition of anti-aliasing layers. The proposed deep prior method outperformed conventional non-learning methods quantitively and qualitatively in numerical simulations and in-vivo data.

This abstract and the presentation materials are available to members only; a login is required.

Join Here