Literature DB >> 8121267

Quantifying MRI geometric distortion in tissue.

T Sumanaweera1, G Glover, S Song, J Adler, S Napel.   

Abstract

We present a method to quantify the MR field inhomogeneity geometric distortion to subpixel accuracy without using objects of known dimensions and without using an external standard such as CT. Our method may be used to quantify the geometric accuracy of MR images of anatomical structures of unknown geometry and also to test any geometry correction scheme. We have quantified the distortion in a tissue phantom and found the largest error to be approximately 2.8 pixels (1.8 mm) for Bo = 1.5 T, G = 3.13 mT/m and FOV = 160 x 160 x 70.7 mm3. We also found that our previously published correction technique reduced the largest error to 0.3 pixels (mu = 0.02 and sigma = 0.07 pixels).

Mesh:

Year:  1994        PMID: 8121267     DOI: 10.1002/mrm.1910310106

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  14 in total

1.  The MR Cap: A single-sided MRI system designed for potential point-of-care limited field-of-view brain imaging.

Authors:  Patrick C McDaniel; Clarissa Zimmerman Cooley; Jason P Stockmann; Lawrence L Wald
Journal:  Magn Reson Med       Date:  2019-06-23       Impact factor: 4.668

2.  Accuracy of 3D cartilage models generated from MR images is dependent on cartilage thickness: laser scanner based validation of in vivo cartilage.

Authors:  Seungbum Koo; Nicholas J Giori; Garry E Gold; Chris O Dyrby; Thomas P Andriacchi
Journal:  J Biomech Eng       Date:  2009-12       Impact factor: 2.097

3.  Head to head comparison of two commercial phantoms used for SRS QA.

Authors:  Vikren Sarkar; Long Huang; Yu-Huei Jessica Huang; Martin W Szegedi; Prema Rassiah-Szegedi; Hui Zhao; Bill J Salter
Journal:  J Radiosurg SBRT       Date:  2016

4.  Distortion correction in whole-body imaging of live mice using a 1-Tesla compact magnetic resonance imaging system.

Authors:  Shigeru Kiryu; Yusuke Inoue; Yoshitaka Masutani; Tomoyuki Haishi; Kohki Yoshikawa; Makoto Watanabe; Kuni Ohtomo
Journal:  Jpn J Radiol       Date:  2011-06-30       Impact factor: 2.374

5.  Quantitative effects of off-resonance related distortion on brain mechanical property estimation with magnetic resonance elastography.

Authors:  Grace McIlvain; Matthew D J McGarry; Curtis L Johnson
Journal:  NMR Biomed       Date:  2021-09-20       Impact factor: 4.044

6.  Quantitative assessment of articular cartilage morphology via EPIC-microCT.

Authors:  L Xie; A S P Lin; M E Levenston; R E Guldberg
Journal:  Osteoarthritis Cartilage       Date:  2008-09-11       Impact factor: 6.576

7.  Phantom-based characterization of distortion on a magnetic resonance imaging simulator for radiation oncology.

Authors:  Ke Colin Huang; Yue Cao; Umar Baharom; James M Balter
Journal:  Phys Med Biol       Date:  2016-01-06       Impact factor: 3.609

8.  The osteoarthritis initiative (OAI) magnetic resonance imaging quality assurance methods and results.

Authors:  E Schneider; M NessAiver; D White; D Purdy; L Martin; L Fanella; D Davis; M Vignone; G Wu; R Gullapalli
Journal:  Osteoarthritis Cartilage       Date:  2008-04-18       Impact factor: 6.576

9.  MRI vs CT-based 2D-3D auto-registration accuracy for quantifying shoulder motion using biplane video-radiography.

Authors:  Mohsen Akbari-Shandiz; Rebekah L Lawrence; Arin M Ellingson; Casey P Johnson; Kristin D Zhao; Paula M Ludewig
Journal:  J Biomech       Date:  2018-09-29       Impact factor: 2.712

10.  Empirical field mapping for gradient nonlinearity correction of multi-site diffusion weighted MRI.

Authors:  Colin B Hansen; Baxter P Rogers; Kurt G Schilling; Vishwesh Nath; Justin A Blaber; Okan Irfanoglu; Alan Barnett; Carlo Pierpaoli; Adam W Anderson; Bennett A Landman
Journal:  Magn Reson Imaging       Date:  2020-11-19       Impact factor: 2.546

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