ArticleMagnetic resonance in medicine2025
Automated fibrosis segmentation from wideband post-contrast
Article in Magnetic resonance in medicine, 2025. 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.
- Article
- Automated fibrosis segmentation from wideband post-contrastMagnetic resonance in medicine · 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
5 authors.
Funding
Abstract
purposePost-contrast
methodsSeven swine received an ischemia-reperfusion myocardial infarction and were imaged at 3 T 4-5 weeks post-infarct with and without an ICD. Mapping-based thresholding was performed using synthetic LGE and artifact-corrected cluster-thresholding methods, both employing connected component filtering. Standard pixel signal intensity thresholding was performed on the conventional LGE without an ICD. Volumetric accuracy is relative to conventional LGE and Dice similarity between SynLGE and cluster-based segmentations were evaluated.
resultsNo statistical significance was observed between LGE volumes without an ICD and both SynLGE and artifact-corrected cluster-threshold volumes with an ICD, when using connected component filtering. Additionally, Dice alignment between SynLGE and cluster-thresholding was high for healthy myocardium (0.96), dense scar (0.83), and dense scar union gray zone (0.91) when artifact correction and connected component filtering were implemented.
conclusionClustering of
Indexed as
Identifiers
What Socratic 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 Socratic graph.