ArticleJournal of applied clinical medical physics2021
Computational approaches to detect small lesions in
Article in Journal of applied clinical medical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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
1 citing paper in PubMed.
- Computational approaches to detect small lesions inJournal of applied clinical medical physics · 2021Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeWhen physicians interpret
methodsRoutinely collected quality assurance test data were processed retrospectively for 65 different
resultsThe three largest cylinders were visible in 100% of cases with a mean visibility score of 3.3 ± 1.2, while the smallest 8-mm cylinder was visible in 58% of cases with a significantly lower mean visibility score of 1.5±1.1 (P < 0.0001). By ROC analysis, the polynomial-fit signal-to-noise ratio was the most accurate at discriminating 8-mm cylinders from the background, with accuracy greater than visual detection (93% ± 2% versus 76% ± 4%, P = 0.0001), and better sensitivity (94% versus 58%, P < 0.0001).
conclusionImage texture analysis metrics are more sensitive than visual impressions for detecting sub-centimeter simulated lesions. Therefore, image texture analysis metrics are potentially clinically useful for
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Registered trials
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