World's Best Scientists 2026 revealed!
Magnetic Resonance Imaging
H-index 23

Magnetic Resonance Imaging

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Medicine 1245 132 174 19

Additional Metrics

Number of Best Scientists*: 334
Documents by Best Scientists*: 347
Top 100 Ranked Scientists*: 10
SCIMAGO H-index: 126
SCIMAGO SJR: 0.63
Impact Factor: 2

Overview

Top Research Topics at Magnetic Resonance Imaging?

The objective of the journal is to combine knowledge in the areas of Nuclear magnetic resonance, Magnetic resonance imaging, Nuclear medicine, Artificial intelligence and Radiology. The research on Nuclear magnetic resonance featured in Magnetic Resonance Imaging combines topics in other fields like Magnetic resonance force microscopy, Spin echo, Physics of magnetic resonance imaging, Magnetic resonance microscopy and Electromagnetic coil. The journal concentrated on Spin echo research, specifically Relaxometry and Nuclear magnetic resonance decoupling.

The concepts on Magnetic resonance imaging presented in Magnetic Resonance Imaging can also apply to other research fields, including Internal medicine, Anatomy, Biomedical engineering and Pathology. Most of the Nuclear medicine studies addressed also intersect with Diffusion MRI. It features Diffusion MRI research that overlaps with concepts in Effective diffusion coefficient.

While work presented in it provided substantial information on Artificial intelligence, it also covered topics in Computer vision and Pattern recognition.

  • Nuclear magnetic resonance (36.12%)
  • Magnetic resonance imaging (30.59%)
  • Nuclear medicine (13.11%)

What are the most cited papers published in the journal?

  • 3D Slicer as an image computing platform for the Quantitative Imaging Network. (2779 citations)
  • Radiomics: the process and the challenges (1045 citations)
  • Magnetic resonance imaging apparatus (913 citations)

Research areas of the most cited articles at Magnetic Resonance Imaging:

The most cited papers primarily focus on research topics in Nuclear magnetic resonance, Magnetic resonance imaging, Nuclear medicine, Artificial intelligence and Pathology. The majority of Nuclear magnetic resonance studies presented in the journal publications zero in on Relaxation (NMR). The Magnetic resonance imaging research presented in the journal papers falls under the domain of Radiology.

What topics the last edition of the journal is best known for?

  • Internal medicine
  • Magnetic resonance imaging
  • Surgery

The previous edition focused in particular on these issues:

Magnetic Resonance Imaging mainly tackles studies in Significant difference, Composite material, SQUID, Alloy and Diffraction. Issues in Significant difference were discussed, taking into consideration concepts from other disciplines like Nuclear medicine, Renal perfusion, Left kidney, Kidney and Reproducibility. While it focused on Kidney, it was also able to explore topics like Perfusion and Coronal plane.

Magnetic Resonance Imaging facilitates discussions on Composite material that incorporate concepts from other fields like Magnetic susceptibility, Magnetic resonance imaging, Phase (matter) and Microscope.

The most cited articles from the last journal are:

  • Feasibility of renal perfusion quantification by Fourier decomposition MRI. (0 citations)
  • Dual-phase Au-Pt alloys free from magnetic susceptibility artifacts in magnetic resonance imaging. (0 citations)
  • Self-supervised learning-based diffeomorphic non-rigid motion estimation for fast motion-compensated coronary MR angiography. (0 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

The top authors publishing in Magnetic Resonance Imaging (based on the number of publications) are:

  • John C. Gore (106 papers) absent at the last edition,
  • Richard C. Semelka (57 papers) absent at the last edition,
  • Bruno Maraviglia (56 papers) absent at the last edition,
  • E. Mark Haacke (52 papers) absent at the last edition,
  • Laurance D. Hall (49 papers) absent at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Only papers with recognized affiliations are considered

The top affiliations publishing in Magnetic Resonance Imaging (based on the number of publications) are:

  • Siemens (200 papers) absent at the last edition,
  • Philips (163 papers) absent at the last edition,
  • University of California, San Francisco (131 papers) absent at the last edition,
  • Vanderbilt University (117 papers) absent at the last edition,
  • General Electric (114 papers) absent at the last edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2022 edition, 0.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 0.00% were posted by at least one author from the top 10 institutions publishing in the journal. Another 0.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 0.00% of all publications and 100.00% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Career Opportunities in the Field of Magnetic Resonance Imaging

While this article has successfully navigated numerous topics related to Magnetic Resonance Imaging (MRI), a considerable section that would enhance its depth is a discussion on career opportunities in MRI field. The field of MRI is quite expansive, offering a range of diverse career paths for individuals with a Magnetic Resonance Imaging-related degree. Radiologic Technologists and MRI Technologists are some of the most common professions in the MRI field. These individuals are responsible for positioning patients properly to get the most accurate images, adjusting imaging equipment, effectively operating the machines to capture images and keeping patient records. Alternatively, there are career opportunities in research and academia for those interested in MRI sciences. Researchers can conduct studies on improving imaging technology, while academics can teach and mentor new students in the field. Apart from these, a career in sales and manufacturing of MRI machines can also be sought. This involves designing, manufacturing, marketing, selling and troubleshooting various types of imaging machines. Finally, one of the most exciting prospects in the MR imaging field is its intersection with the emerging field of Artificial Intelligence, opening up cutting-edge opportunities like developing AI algorithms to interpret MRI scans. Considering all these career prospects in the field, it's natural for one to wonder about the process of starting a career in a related healthcare sector. For instance, if you're intrigued by the role of Radiologic Technologists, a useful resource could be learning {anchor}how to be a nurse in Colorado where you will learn about the dynamics of starting a healthcare career. Remember, any role in the MRI field could be a gateway to an interesting, rewarding career. With technological advancements in imaging, the demand for professionals in this field only continues to grow, resulting in a vibrant range of future opportunities.

Top Publications

  • Artificial intelligence in medical imaging.

    John C. Gore

    (2020)
    182 Citations
  • STrategically Acquired Gradient Echo (STAGE) imaging, part III: Technical advances and clinical applications of a rapid multi-contrast multi-parametric brain imaging method.

    E. Mark Haacke;Yongsheng Chen;David Utriainen;Bo Wu

    (2020)
    53 Citations
  • Free-running cardiac magnetic resonance fingerprinting: Joint T1/T2 map and Cine imaging.

    O. Jaubert;G. Cruz;A. Bustin;T. Schneider

    (2020)
    46 Citations
  • Radiomic prediction of mutation status based on MR imaging of lung cancer brain metastases

    Bihong T. Chen;Taihao Jin;Ningrong Ye;Isa Mambetsariev

    (2020)
    42 Citations
  • A multi-scale variational neural network for accelerating motion-compensated whole-heart 3D coronary MR angiography.

    Niccolo Fuin;Aurelien Bustin;Thomas Küstner;Ilkay Oksuz

    (2020)
    41 Citations
  • Accuracy and reproducibility of automated white matter hyperintensities segmentation with lesion segmentation tool: A European multi-site 3T study

    Federica Ribaldi;Daniele Altomare;Jorge Jovicich;Clarissa Ferrari

    (2021)
    32 Citations
  • 10.5 T MRI static field effects on human cognitive, vestibular, and physiological function.

    Andrea Grant;Gregory J. Metzger;Pierre François Van de Moortele;Gregor Adriany

    (2020)
    30 Citations
  • Are multi-contrast magnetic resonance images necessary for segmenting multiple sclerosis brains? A large cohort study based on deep learning.

    Ponnada A. Narayana;Ivan Coronado;Sheeba J. Sujit;Xiaojun Sun

    (2020)
    27 Citations
  • Clinical feasibility of an abdominal thin-slice breath-hold single-shot fast spin echo sequence processed using a deep learning-based noise-reduction approach.

    (2022)
    23 Citations
  • Rapid whole-brain quantitative magnetization transfer imaging using 3D selective inversion recovery sequences

    Matthew J. Cronin;Junzhong Xu;Francesca Bagnato;Daniel F. Gochberg;Daniel F. Gochberg

    (2020)
    23 Citations

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Best Scientists Contributing to This Journal