ReviewRadiologia brasileira
Image quality in diagnostic radiology: a guide to methodologies for radiologists.
Review in Radiologia brasileira. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Using of artificial intelligence to evaluate image quality for interproximal bone level assessment on bitewing radiographs.Imaging science in dentistry · 2026Article
- Computed tomography image quality with high-flow contrast via high-pressure central venous catheter in critically ill patients.Critical care (London, England) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of this article is to provide a comprehensive guide to image quality assessment in diagnostic radiology, emphasizing practical methodologies for radiologists. The goal is to improve diagnostic accuracy and patient care on the basis of the understanding and application of quantitative and qualitative metrics in clinical practice and research. We conducted a review of the literature in the PubMed, Scopus, Web of Science, and Embase databases. The search terms included "image quality in radiology", "quantitative and qualitative assessment", "modulation transfer function", "signal-to-noise ratio", "contrast-to-noise ratio", "radiation dose optimization", and "artificial intelligence in image quality assessment". The review identified the main methodologies for image quality assessment. We analyzed these metrics for their applicability in clinical settings, highlighting their benefits and limitations. In addition, we discuss qualitative methods such as visual assessment, the assessment of contrast/density, and peer review. This guide fills a gap in the literature by providing accessible, practical knowledge for general radiologists. Ongoing research, education, and technological development are essential to advance the field and ensure high standards in radiology practice.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.