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Journal of Medical Imaging
H-index 22

Journal of Medical Imaging

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Engineering and Technology 767 24 63 11
Medicine 1424 93 125 17

Additional Metrics

Number of Best Scientists*: 267
Documents by Best Scientists*: 322
Top 100 Ranked Scientists*: 6
SCIMAGO H-index: 54
SCIMAGO SJR: 0.523
Impact Factor: 1.7

Overview

Top Research Topics at Journal of medical imaging?

The journal investigates studies in Radiology, Magnetic resonance imaging, Tomography, Pathology and Nuclear medicine. The research on Radiology featured in the journal combines topics in other fields like Differential diagnosis and Lesion, Surgery. Embolization is a focus of the presented Surgery works and it dives deep in Embolization.

The studies tackled, which mainly focus on Magnetic resonance imaging, apply to Anatomy as well. The Tomography study tackling the subject of Spiral ct is the focus of it. The works on Pathology deal in particular with Pathological.

The Angiography study tackled is a key component of adjacent topics in the area of Artery.

  • Radiology (57.16%)
  • Magnetic resonance imaging (18.58%)
  • Tomography (15.14%)

What are the most cited papers published in the journal?

  • Digital mammographic tumor classification using transfer learning from deep convolutional neural networks (281 citations)
  • Mitosis detection in breast cancer pathology images by combining handcrafted and convolutional neural network features (203 citations)
  • DeepLesion: automated mining of large-scale lesion annotations and universal lesion detection with deep learning (186 citations)

Research areas of the most cited articles at Journal of medical imaging:

The most cited publications explore disciplines such as Artificial intelligence, Pattern recognition, Image segmentation, Medical imaging and Convolutional neural network. The journal articles explore research in Computer vision and overlapping concepts in Visualization to expand the discourse in Artificial intelligence. The published articles hold forums on Image segmentation that merge themes from other disciplines such as Ground truth, Magnetic resonance imaging, Radiology and Receiver operating characteristic.

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

  • Internal medicine
  • Surgery
  • Radiology

The previous edition focused in particular on these issues:

The objective of Journal of medical imaging is to combine knowledge in the areas of Artificial intelligence, Pattern recognition, Image segmentation, Image quality and Imaging phantom. Journal of medical imaging focuses on Artificial intelligence as well as the interrelated topic of Computer vision. The presented studies in Feature extraction fall within the purview of Pattern recognition but it also intertwines with topics in Sensitivity (control systems).

The Image segmentation research discussed is included in the broader subject of Segmentation. The study of Magnetic resonance imaging and how it intertwines with concepts under Internal medicine were explored in the presented Segmentation research. While Image quality is the focus of Journal of medical imaging, it also provided insights into the studies of Image resolution, Algorithm, Iterative reconstruction and Projection (set theory).

The most cited articles from the last journal are:

  • Deep CNN models for predicting COVID-19 in CT and x-ray images (4 citations)
  • Review of the efficacy of infrared thermography for screening infectious diseases with applications to COVID-19. (3 citations)
  • COVID-19 detection and heatmap generation in chest x-ray images (3 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 Journal of medical imaging (based on the number of publications) are:

  • Maryellen L. Giger (34 papers) published 3 papers at the last edition, 2 less than at the previous edition,
  • Ehsan Samei (27 papers) published 2 papers at the last edition, 1 less than at the previous edition,
  • Shuai Leng (17 papers) published 1 paper at the last edition, 1 less than at the previous edition,
  • Cynthia H. McCollough (16 papers) published 1 paper at the last edition, 1 less than at the previous edition,
  • Jeffrey H. Siewerdsen (15 papers) published 3 papers at the last edition the same number as at the previous 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 Journal of medical imaging (based on the number of publications) are:

  • Shandong University (140 papers) absent at the last edition,
  • Shanghai Jiao Tong University (66 papers) absent at the last edition,
  • Capital Medical University (57 papers) absent at the last edition,
  • University of Chicago (56 papers) published 7 papers at the last edition, 3 less than at the previous edition,
  • Nanjing Medical University (45 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 2021 edition, 17.32% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 18.10% were posted by at least one author from the top 10 institutions publishing in the journal. Another 13.33% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 20.00% of all publications and 48.57% 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.

Top Publications

  • Virtual clinical trials in medical imaging: a review

    Ehsan Abadi;William P. Segars;Benjamin M. W. Tsui;Paul E. Kinahan

    (2020)
    204 Citations
  • Computed tomography recent history and future perspectives.

    Jiang Hsieh;Thomas Flohr

    (2021)
    83 Citations
  • Toward fairness in artificial intelligence for medical image analysis: identification and mitigation of potential biases in the roadmap from data collection to model deployment.

    (2023)
    61 Citations
  • Quick guide on radiology image pre-processing for deep learning applications in prostate cancer research.

    Samira Masoudi;Stephanie A. A. Harmon;Sherif Mehralivand;Stephanie M. Walker

    (2021)
    55 Citations
  • How CT happened: the early development of medical computed tomography.

    Raymond A Schulz;Jay A Stein;Norbert J Pelc

    (2021)
    44 Citations
  • Overall survival prediction in glioblastoma patients using structural magnetic resonance imaging (MRI): advanced radiomic features may compensate for lack of advanced MRI modalities

    Spyridon Bakas;Gaurav Shukla;Gaurav Shukla;Hamed Akbari;Guray Erus

    (2020)
    44 Citations
  • Harmonization of radiomic features of breast lesions across international DCE-MRI datasets

    Heather M. Whitney;Hui Li;Yu Ji;Peifang Liu

    (2020)
    36 Citations
  • Detective quantum efficiency of photon-counting CdTe and Si detectors for computed tomography: a simulation study

    Mats Persson;Adam Wang;Norbert J. Pelc

    (2020)
    35 Citations
  • Deep learning segmentation of glomeruli on kidney donor frozen sections

    (2021)
    28 Citations
  • SPIE-AAPM-NCI BreastPathQ Challenge: an image analysis challenge for quantitative tumor cellularity assessment in breast cancer histology images following neoadjuvant treatment

    Nicholas A. Petrick;Shazia Akbar;Kenny H. H. Cha;Sharon Nofech-Mozes

    (2021)
    27 Citations

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Best Scientists Contributing to This Journal

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