ArticleCancers2023
Assessment of Variabilities in Lung-Contouring Methods on CBCT Preclinical Radiomics Outputs.
Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Ensemble methods and partially-supervised learning for accurate and robust automatic murine organ segmentation.Scientific reports · 2025Article
- Radiomics as a measure superior to common similarity metrics for tumor segmentation performance evaluation.Journal of applied clinical medical physics · 2024Article
- A comparative analysis of preclinical computed tomography radiomics using cone-beam and micro-computed tomography scanners.Physics and imaging in radiation oncology · 2024Article
- Exploring the Application of the Artificial-Intelligence-Integrated Platform 3D Slicer in Medical Imaging Education.Diagnostics (Basel, Switzerland) · 2024Review
- Development and optimisation of a preclinical cone beam computed tomography-based radiomics workflow for radiation oncology research.Physics and imaging in radiation oncology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Radiomics image analysis has the potential to uncover disease characteristics for the development of predictive signatures and personalised radiotherapy treatment. Inter-observer and inter-software delineation variabilities are known to have downstream effects on radiomics features, reducing the reliability of the analysis. The purpose of this study was to investigate the impact of these variabilities on radiomics outputs from preclinical cone-beam computed tomography (CBCT) scans. Inter-observer variabilities were assessed using manual and semi-automated contours of mouse lungs (
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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.