Special Issue "Magnetic Resonance Imaging"

A special issue of Journal of Imaging (ISSN 2313-433X).

Deadline for manuscript submissions: closed (30 June 2017)

Special Issue Editor

Guest Editor
Prof. Dr. David Moratal

Department of Electronic Engineering & Center for Biomaterials and Tissue Engineering, Universitat Politècnica de València, Cami de Vera, s/n, 46022 Valencia, Spain
Website | E-Mail
Interests: magnetic resonance imaging; MRI, neuroimaging; cardiac MRI; machine learning; texture analysis; brain connectivity; functional MRI; multimodal image analysis; MR imaging biomarkers

Special Issue Information

Dear Colleagues,

Magnetic resonance imaging (MRI), also known as nuclear magnetic resonance imaging, is the medical imaging technique that provides the best soft tissue contrast among the existing medical imaging modalities, creating detailed images of the inside of the body by means of strong magnetic fields, radio waves, and magnetic field gradients.

In this Special Issue, we intend to collect experiences of leading scientists and invite front-line researchers and authors to submit original research and review articles on magnetic resonance imaging. This Special Issue intends also to be a resource tool for people who are new to the world of MRI.

Potential topics of this Special Issue include, but are not limited to, the use of technology, as well as novel image processing algorithms on:

  • Head MRI
  • Cardiac MRI
  • Specialized applications as prostate or knee
  • Pharmacokinetic modelling in MRI
  • Diffusion MRI
  • Tensor imaging
  • Functional MRI
  • Phase-contrast MRI
  • MR angiography
  • MR biomarkers
  • MRI safety
  • MRI physics
  • MRI acceleration strategies
  • Hardware design and development in MRI
  • Educational tools to study basic principles of MR imaging
  • Future of MRI

Papers must present novel results, or the advancement of previously published data, and the matter should be dealt with scientific rigor.

Prof. Dr. David Moratal
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Imaging is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) is waived for well-prepared manuscripts submitted to this issue. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • magnetic resonance imaging
  • nuclear magnetic resonance imaging
  • MRI
  • magnetic resonance imaging biomarkers
  • pharmacokinetic modelling in MRI
  • neuroimaging
  • cancer imaging
  • cardiac imaging
  • clinical applications
  • medical imaging
  • diffusion imaging
  • tensor imaging
  • functional imaging
  • phase-contrast magnetic resonance imaging
  • magnetic resonance angiography
  • MRI safety
  • MRI physical principles
  • MRI acceleration strategies
  • hardware design and development in MRI
  • educational tools in medical imaging

Published Papers (1 paper)

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Research

Open AccessArticle Assessment of Geometric Distortion in Six Clinical Scanners Using a 3D-Printed Grid Phantom
J. Imaging 2017, 3(3), 28; doi:10.3390/jimaging3030028
Received: 26 May 2017 / Revised: 27 June 2017 / Accepted: 15 July 2017 / Published: 18 July 2017
PDF Full-text (2370 KB) | HTML Full-text | XML Full-text
Abstract
A cost-effective regularly structured three-dimensional (3D) printed grid phantom was developed to enable the quantification of machine-related magnetic resonance (MR) distortion. This phantom contains reference features, “point-like” objects, or vertices, which resulted from the intersection of mesh edges in 3D space. 3D distortions
[...] Read more.
A cost-effective regularly structured three-dimensional (3D) printed grid phantom was developed to enable the quantification of machine-related magnetic resonance (MR) distortion. This phantom contains reference features, “point-like” objects, or vertices, which resulted from the intersection of mesh edges in 3D space. 3D distortions maps were computed by comparing the locations of corresponding features in both MR and computer tomography (CT) data sets using normalized cross correlation. Results are reported for six MRI scanners at both 1.5 T and 3.0 T field strengths within our institution. Mean Euclidean distance error for all MR volumes in this study, was less than 2 mm. The maximum detected error for the six scanners ranged from 2.4 mm to 6.9 mm. The conclusions in this study agree well with previous studies that indicated that MRI is quite accurate near the centre of the field but is more spatially inaccurate toward the edges of the magnetic field. Full article
(This article belongs to the Special Issue Magnetic Resonance Imaging)
Figures

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