ArticleNature communications2026
Automatic optimization of flat-field corrections by evaluation and enhancement (EVEN) in multimodal optical microscopy.
Article in Nature communications, 2026. 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
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
1 citing paper in PubMed.
- Automatic optimization of flat-field corrections by evaluation and enhancement (EVEN) in multimodal optical microscopy.Nature communications · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Uneven illumination affects all images acquired by optical microscopes, especially large, multicolour and nonlinear measurements. Although removal is possible with various algorithms, evaluating raw and processed images is challenging due to the lack of established workflows for image quality assessment. This manuscript describes a machine learning-based method, EVEN (Evaluation and Enhancement), to assess and optimise corrections in optical microscopy. EVEN integrates quantitative image metrics into a Linear Discriminant Analysis model to detect and predict image quality, automatically optimising corrections. The method can be integrated into the optical microscopy pipeline to simplify further processing and analysis. Here, we show the implementation and application of EVEN in different processing scenarios, including multimodal nonlinear imaging of human and neck tissue slices and multichannel fluorescence measurements of stained cells, demonstrating its capability to automatically optimise image quality by assessing single-channel corrections.
Identifiers
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.