Literature DB >> 30529225

The effect of motion correction interpolation on quantitative T1 mapping with MRI.

Amitay Nachmani1, Roey Schurr2, Leo Joskowicz1, Aviv A Mezer3.   

Abstract

Quantitative magnetic resonance imaging (qMRI) is a technique for mapping the physical properties of the underlying tissue using several MR images with different contrasts. To overcome subject motion between the acquired images, it is necessary to register the images to a common reference frame. A drawback of registration is the use of interpolation and resampling techniques, which can introduce artifacts into the interpolated data. These artifacts could have unfavorable effects on the accuracy of the estimated tissue's physical properties. Here, we quantified the error of interpolation and resampling on T1-weighted images and studied its effects on the mapping of the longitudinal relaxation time (T1) using variable flip angles. We simulated T1-weighted images and calculated the transformation error resulting from interpolation and resampling. We found that the error is a function of the image contrast (i.e., flip angle) and of the translation and rotation of the image. Furthermore, we found that the error in the T1-weighted images has a substantial effect on the T1 estimation, of the order of 10% of the signal in the brain's gray and white matter. Hence, minimizing the registration error can enable more accurate in vivo modeling of brain microstructure.
Copyright © 2018 Elsevier B.V. All rights reserved.

Keywords:  Interpolation and resampling error; Motion; Quantitative magnetic resonance imaging; Registration; T1 map

Mesh:

Year:  2018        PMID: 30529225     DOI: 10.1016/j.media.2018.11.012

Source DB:  PubMed          Journal:  Med Image Anal        ISSN: 1361-8415            Impact factor:   8.545


  3 in total

1.  Three-dimensional motion-corrected T1 relaxometry with MPnRAGE.

Authors:  Steven Kecskemeti; Andrew L Alexander
Journal:  Magn Reson Med       Date:  2020-04-17       Impact factor: 4.668

2.  An MRI-based radiomics-clinical nomogram for the overall survival prediction in patients with hypopharyngeal squamous cell carcinoma: a multi-cohort study.

Authors:  Juan Chen; Shanhong Lu; Yitao Mao; Lei Tan; Guo Li; Yan Gao; Pingqing Tan; Donghai Huang; Xin Zhang; Yuanzheng Qiu; Yong Liu
Journal:  Eur Radiol       Date:  2021-10-19       Impact factor: 7.034

3.  Impact of image preprocessing methods on reproducibility of radiomic features in multimodal magnetic resonance imaging in glioblastoma.

Authors:  Hajar Moradmand; Seyed Mahmoud Reza Aghamiri; Reza Ghaderi
Journal:  J Appl Clin Med Phys       Date:  2019-12-27       Impact factor: 2.102

  3 in total

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