@inproceedings{88b15d711a514ff69a9a82b4617e9c67,
title = "Parallel magnetic resonance imaging reconstruction algorithm by 3-dimension directional Haar tight framelet regularization",
abstract = "In this paper, a 3-dimension directional Haar tight framelet (3DHF) is used to detect the related features between coil images in parallel magnetic resonance imaging (pMRI). Such a Haar tight framelet has an extremely simple geometric structure in the sense that all the high-pass filters in its underlying filter bank have only two nonzero coefficients with opposite signs. A pMRI optimization model, which we coined 3DHF-SPIRiT, by regularizing the 3DHF features on the 3-D coil image data is proposed to reduce the aliasing artifacts caused by the downsampling operation in the k-space (Fourier) domain, which can be solved by alternating direction method of multipliers (ADMM) scheme. Numerical experiments are provided to demonstrate the superiority and efficiency of our 3DHF-SPIRiT model.",
keywords = "3-D regularization, ADMM, directional Haar tight framelets, GRAPPA, pMRI, SENSE, SPIRiT",
author = "Yan-Ran Li and Xiaosheng Zhuang",
year = "2019",
month = aug,
doi = "10.1117/12.2528788",
language = "English",
isbn = "9781510629691",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Ville, {Dimitri Van De} and Manos Papadakis and Lu, {Yue M.}",
booktitle = "Wavelets and Sparsity XVIII",
address = "United States",
note = "Conference on Wavelets and Sparsity XVIII ; Conference date: 13-08-2019 Through 15-08-2019",
}