ReviewFrontiers in bioengineering and biotechnology2025
Imaging flow cytometry: from high - resolution morphological imaging to innovation in high - throughput multidimensional biomedical analysis.
Review in Frontiers in bioengineering and biotechnology, 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.
- Generalizable self-supervised learning for imaging flow cytometry on multi-dataset leukocyte differential.Microsystems & nanoengineering · 2026Article
- Imaging Flow Cytometry as a Molecular Biology Tool: From Cell Morphology to Molecular Mechanisms.International journal of molecular sciences · 2025Review
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
No grant is acknowledged in the PubMed record.
Abstract
Imaging flow cytometry (IFC), as an extension of conventional flow cytometry, has emerged as a cutting-edge cellular analysis tool by integrating high-resolution imaging technology, and has shown significant potential and application value in biomedical research. In this paper, we comprehensively review the evolution of IFC from its early theoretical development to its current mature application, and explain its working principle, unique advantages, and the current status of its application in several biomedical fields. The paper focuses on how IFC integrates high-throughput and morphological imaging, highlighting its key role in cell biology, immunology, oncology, and environmental monitoring. Furthermore, the paper addresses the challenges and opportunities in data analysis, and proposes the potential of artificial intelligence (AI) and machine learning technologies to drive its progress. The paper concludes with an outlook on the future of IFC, predicting its application in emerging research areas and emphasizing the role of continuous technological innovation in driving the development of the field. It aims to provide researchers with a comprehensive view of IFC to promote its widespread application in biomedical research.
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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.