ArticleScientific reports2016
DIC image reconstruction using an energy minimization framework to visualize optical path length distribution.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Identifying Heterogeneous Micromechanical Properties of Biological Tissues via Physics-Informed Neural Networks.Small methods · 2025Article
- CMTT-JTracker: a fully test-time adaptive framework serving automated cell lineage construction.Briefings in bioinformatics · 2024Article
- Biomolecular condensates and disease pathogenesis.Science China. Life sciences · 2024Review
- Article
- Automated identification and tracking of cells in Cytometry of Reaction Rate Constant (CRRC).PloS one · 2023Article
- Automatic deep learning-driven label-free image-guided patch clamp system.Nature communications · 2021Article
- Cell segmentation methods for label-free contrast microscopy: review and comprehensive comparison.BMC bioinformatics · 2019Review
- Screening out irrelevant cell-based models of disease.Nature reviews. Drug discovery · 2016Review
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
No grant is acknowledged in the PubMed record.
Abstract
Label-free microscopy techniques have numerous advantages such as low phototoxicity, simple setup and no need for fluorophores or other contrast materials. Despite their advantages, most label-free techniques cannot visualize specific cellular compartments or the location of proteins and the image formation limits quantitative evaluation. Differential interference contrast (DIC) is a qualitative microscopy technique that shows the optical path length differences within a specimen. We propose a variational framework for DIC image reconstruction. The proposed method largely outperforms state-of-the-art methods on synthetic, artificial and real tests and turns DIC microscopy into an automated high-content imaging tool. Image sets and the source code of the examined algorithms are made publicly available.
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.