European Radiology Experimental

Scope & Guideline

Pioneering the Future of Medical Imaging

Introduction

Immerse yourself in the scholarly insights of European Radiology Experimental with our comprehensive guidelines detailing its aims and scope. This page is your resource for understanding the journal's thematic priorities. Stay abreast of trending topics currently drawing significant attention and explore declining topics for a full picture of evolving interests. Our selection of highly cited topics and recent high-impact papers is curated within these guidelines to enhance your research impact.
LanguageEnglish
ISSN-
PublisherSPRINGER WIEN
Support Open AccessNo
Country-
Type-
Converge-
AbbreviationEUR RADIOL EXP / Eur. Radiol. Exp.
Frequency1 issue/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressPrinz-Eugen-Strasse 8-10, A-1040 Vienna, AUSTRIA

Aims and Scopes

European Radiology Experimental focuses on advancing the field of radiology through innovative research, particularly in the integration of artificial intelligence, imaging techniques, and radiomics. The journal emphasizes the application of cutting-edge methodologies to enhance diagnostic accuracy and treatment efficacy.
  1. Artificial Intelligence in Imaging:
    The journal consistently publishes research on the application of AI and machine learning for image analysis, segmentation, and diagnosis across various imaging modalities.
  2. Advanced Imaging Techniques:
    There is a significant focus on novel imaging techniques, including photon-counting CT, high-resolution MRI, and dual-energy CT, aimed at improving image quality and diagnostic capabilities.
  3. Radiomics and Biomarkers:
    Research on radiomics, which involves extracting quantitative features from medical images to predict clinical outcomes, is a core area of interest, particularly in oncology.
  4. Interventional Radiology Innovations:
    The journal explores advancements in interventional radiology, including novel techniques and tools for minimally invasive procedures, which enhance patient outcomes.
  5. Comparative Studies of Imaging Modalities:
    A consistent theme is the comparative analysis of different imaging modalities to establish best practices and improve diagnostic protocols.
Recent publications in European Radiology Experimental highlight emerging trends and themes that reflect the evolving landscape of radiological research, particularly in technology and methodology.
  1. Integration of AI and Machine Learning:
    There is a significant increase in studies employing AI algorithms for image analysis, segmentation, and predictive modeling, showcasing the growing reliance on technology to enhance diagnostic accuracy.
  2. Photon-Counting CT Technology:
    Recent papers highlight advancements in photon-counting CT, which offers improved image quality and lower radiation doses, signifying a trend towards more efficient imaging solutions.
  3. Radiomics and Personalized Medicine:
    Emerging research focuses on radiomics as a tool for personalized medicine, where imaging biomarkers are used to tailor treatments based on individual patient characteristics.
  4. Non-Invasive Imaging Biomarkers:
    The trend towards non-invasive techniques for assessing disease states, such as using radiomic features for cancer prognosis, is gaining traction, reflecting a shift towards patient-centered approaches.
  5. Interdisciplinary Research:
    There is a growing trend in interdisciplinary studies that combine imaging with other fields such as genetics, pathology, and machine learning, aiming for comprehensive approaches to healthcare challenges.

Declining or Waning

While European Radiology Experimental continues to expand its research horizons, certain themes have shown a decline in prominence over recent years, indicating a potential shift in focus within the field.
  1. Traditional Imaging Techniques:
    There appears to be a waning interest in conventional imaging techniques, such as standard X-rays and basic ultrasound, as research increasingly gravitates towards advanced modalities like CT and MRI.
  2. Basic Radiographic Studies:
    The journal has seen fewer publications focused on basic radiographic studies without the integration of AI or advanced imaging technology, suggesting a preference for more innovative approaches.
  3. Generalized Clinical Applications:
    Research that does not employ specific imaging innovations or advanced methodologies is becoming less common, as the journal emphasizes studies with clear technological advancements.

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