ArticleAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference2024
Noise effect analysis and pulmonary perfusion estimation in electrical impedance tomography.
Article in Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2024. 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.
- Supervised and unsupervised learning for lung perfusion data segmentation in electrical impedance tomography.Biomedical physics & engineering express · 2025Article
- Supervised and unsupervised learning for lung perfusion data segmentation in electrical impedance tomography.Biomedical physics & engineering express · 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
6 authors.
Funding
Abstract
Electrical Impedance Tomography (EIT) is a non-invasive imaging technique used to monitor mechanically ventilated patients at the bedside. This study focuses on evaluating the estimation of pulmonary perfusion and the effects of two common noise sources on the outcomes of a hypertonic saline contrast bolus procedure. We used the first-pass kinetics modeling in EIT data to estimate purely lung and hybrid pixels. Furthermore, we analyzed how signal drift and cardiac partial volume effect can yield misleading outcomes. If left uncompensated, the drift noise showed an overestimation of 33%, while the cardiac partial volume effect showed an underestimation of 13.9% in the maximum slope value. We evaluated the model performance using simulated and actual data within physiologically feasible limits.
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What OpenQuestion 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 OpenQuestion graph.