ArticlePloS one2017
A Probabilistic Method for Estimation of Bowel Wall Thickness in MR Colonography.
Article in PloS one, 2017. 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
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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
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Who cites it
2 citing papers in PubMed.
- Curved planar reformatting and convolutional neural network-based segmentation of the small bowel for visualization and quantitative assessment of pediatric Crohn's disease from MRI.Journal of magnetic resonance imaging : JMRI · 2019Article
- Semi-automatic bowel wall thickness measurements on MR enterography in patients with Crohn's disease.The British journal of radiology · 2017Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
MRI has recently been applied as a tool to quantitatively evaluate the response to therapy in patients with Crohn's disease, and is the preferred choice for repeated imaging. Bowel wall thickness on MRI is an important biomarker of underlying inflammatory activity, being abnormally increased in the acute phase and reducing in response to successful therapy; however, a poor level of interobserver agreement of measured thickness is reported and therefore a system for accurate, robust and reproducible measurements is desirable. We propose a novel method for estimating bowel wall-thickness to improve the poor interobserver agreement of the manual procedure. We show that the variability of wall thickness measurement between the algorithm and observer measurements (0.25mm ± 0.81mm) has differences which are similar to observer variability (0.16mm ± 0.64mm).
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