ArticleJournal of applied clinical medical physics2024
Automated size-specific dose estimates framework in thoracic CT using convolutional neural network based on U-Net model.
Article in Journal of applied clinical medical physics, 2024. 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.
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Who cites it
1 citing paper in PubMed.
- Automated size-specific dose estimates framework in thoracic CT using convolutional neural network based on U-Net model.Journal of applied clinical medical physics · 2024Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThis study aimed to develop an automated method that uses a convolutional neural network (CNN) for calculating size-specific dose estimates (SSDEs) based on the corrected effective diameter (D
methodsTransaxial images obtained from 108 adult patients who underwent non-contrast thoracic CT scans were analyzed. To calculate the D
resultsHigh agreement was obtained between the manual and automated methods for calculating the D
conclusionThe proposed automated framework using a CNN offers a reliable and efficient solution for determining the D
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Registered trials
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