Accelerated MR whole brain imaging with sheared voxel imaging using aliasing separation gradients

Min Oh Kim, Joonsung Lee, Sang Young Zho, Dong Hyun Kim

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Purpose: To accelerate data acquisition by undersampling phase encoding (PE) lines in MR imaging, an aliasing separation method by applying additional encoding gradients which result in voxel shape modification is proposed. Methods: An imaging technique which achieves two directional accelerations by undersampling both PE lines in 3D imaging with aliasing separation gradients is proposed. A simple and fast reconstruction process using shift correction or gridding is followed. Phantom and in vivo experiments are performed to show the characteristics and acceleration capability of the proposed method. Further acceleration is achieved by combining with parallel acquisition techniques. Results: The proposed technique shows anisotropic resolution pattern due to voxel shearing which increases proportionally with the acceleration factor. This characteristic is analyzed in both image domain and k-space and is illustrated by grid phantom imaging results. In in vivo experiment, 3D imaging results are presented with 6× acceleration using the proposed technique and ∼12× acceleration combining with parallel imaging technique. Conclusions: By applying separation gradients along both PE directions in 3D MR imaging, aliasing artifacts have been successfully separated and a high acceleration is achieved for whole brain 3D MR imaging with slight blurring due to voxel shearing.

Original languageEnglish
Article number062301
JournalMedical physics
Volume40
Issue number6
DOIs
Publication statusPublished - 2013 Jun

Bibliographical note

Funding Information:
This work is supported by the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government (MEST) (Grant No. 2012-009903) and by the Ministry of Knowledge Economy (MKE) and Korea Institute for Advancement in Technology (KIAT) through the Workforce Development Program in Strategic Technology.

All Science Journal Classification (ASJC) codes

  • Biophysics
  • Radiology Nuclear Medicine and imaging

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