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European Radiology Experimental is a peer-reviewed journal published by Springer Nature, covering Advanced X-ray and CT Imaging, Radiomics and Machine Learning in Medical Imaging, MRI in cancer diagnosis.
| Publisher | Springer Nature |
|---|---|
| Reference style | Superscript numbered (Nature) Superscript — small raised numerals in the text 1. Smith, A., Jones, B. & Lee, C. A representative article title. European Radiology Experimental 12, 45–58 (2023).
Formats any DOI in European Radiology Experimental style. No sign-up. |
| Publishes research in | Advanced X-ray and CT Imaging Radiomics and Machine Learning in Medical Imaging MRI in cancer diagnosis Advanced MRI Techniques and Applications Radiation Dose and Imaging |
| ISSN | 2509-9280 |
| Citation impact (2-yr) | 5.02 |
| h-index | 48 |
| i10-index | 278 |
| Total citations | 12,575 |
| Article processing charge | $1,815 |
| Open access | Yes |
| Top institutions publishing here | University of Milan |
| Journal website | eurradiolexp.springeropen.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Radiomics is an emerging translational field of research aiming to extract mineable high-dimensional data from clinical images. The radiomic process can be divided into distinct steps with definable inputs and outputs, such as image acquisition and reconstruction, image segmentation, features extraction and qualification, analysis, and model building. Each step needs careful evaluation for the construction…
One of the most promising areas of health innovation is the application of artificial intelligence (AI), primarily in medical imaging. This article provides basic definitions of terms such as "machine/deep learning" and analyses the integration of AI into radiology. Publications on AI have drastically increased from about 100-150 per year in 2007-2008 to 700-800 per…
BACKGROUND: Automated segmentation of anatomical structures is a crucial step in image analysis. For lung segmentation in computed tomography, a variety of approaches exists, involving sophisticated pipelines trained and validated on different datasets. However, the clinical applicability of these approaches across diseases remains limited. METHODS: We compared four generic deep learning approaches trained on various…
Here, we summarise the unresolved debate about p value and its dichotomisation. We present the statement of the American Statistical Association against the misuse of statistical significance as well as the proposals to abandon the use of p value and to reduce the significance threshold from 0.05 to 0.005. We highlight reasons for a conservative…
Precision and planning are key to reconstructive surgery. Augmented reality (AR) can bring the information within preoperative computed tomography angiography (CTA) imaging to life, allowing the surgeon to 'see through' the patient's skin and appreciate the underlying anatomy without making a single incision. This work has demonstrated that AR can assist the accurate identification, dissection…
