ReviewBioinformatics (Oxford, England)2008
Bioimage informatics: a new area of engineering biology.
Review in Bioinformatics (Oxford, England), 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 117 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
117 citing papers in PubMed.
- Article
- PixelDeck: A local-first media library manager for biomedical imaging.bioRxiv : the preprint server for biology · 2026Article
- Deep learning-based segmentation of 2D projection-derived overlapping prospore membrane in yeast.Cell structure and function · 2025Article
- SlicerMorph photogrammetry: an open-source photogrammetry workflow for reconstructing 3D models.Biology open · 2025Article
- Sharing massive biomedical data at magnitudes lower bandwidth using implicit neural function.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Cellular harmonics for the morphology-invariant analysis of molecular organization at the cell surface.Nature computational science · 2023Article
- Lipid droplets: a cellular organelle vital in cancer cells.Cell death discovery · 2023Review
- Bioimage informatics: Investing in software usability is essential.PLoS biology · 2023Article
- Image Classification and Automated Machine Learning to Classify Lung Pathologies in Deceased Feedlot Cattle.Veterinary sciences · 2023Article
- Big Data in Gastroenterology Research.International journal of molecular sciences · 2023Review
- Prognostic Analysis of Human Pluripotent Stem Cells Based on Their Morphological Portrait and Expression of Pluripotent Markers.International journal of molecular sciences · 2022Article
- Applications of Neural Networks in Biomedical Data Analysis.Biomedicines · 2022Review
- Lipid droplets as endogenous intracellular microlenses.Light, science & applications · 2021Article
- Analytics and visualization tools to characterize single-cell stochasticity using bacterial single-cell movie cytometry data.BMC bioinformatics · 2021Article
- Mechanical Intermittent Compression Affects the Progression Rate of Malignant Melanoma Cells in a Cycle Period-Dependent Manner.Diagnostics (Basel, Switzerland) · 2021Article
- Microphysiological System for High-Throughput Computer Vision Measurement of Microtissue Contraction.ACS sensors · 2021Article
- Automated mesenchymal stem cell segmentation and machine learning-based phenotype classification using morphometric and textural analysis.Journal of medical imaging (Bellingham, Wash.) · 2021Article
- ACDC: Automated Cell Detection and Counting for Time-Lapse Fluorescence Microscopy.Applied sciences (Basel, Switzerland) · 2020Article
- MaRe: Processing Big Data with application containers on Apache Spark.GigaScience · 2020Article
- Frontiers in Intravital Multiphoton Microscopy of Cancer.Cancer reports (Hoboken, N.J.) · 2020Review
57 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, the deluge of complicated molecular and cellular microscopic images creates compelling challenges for the image computing community. There has been an increasing focus on developing novel image processing, data mining, database and visualization techniques to extract, compare, search and manage the biological knowledge in these data-intensive problems. This emerging new area of bioinformatics can be called 'bioimage informatics'. This article reviews the advances of this field from several aspects, including applications, key techniques, available tools and resources. Application examples such as high-throughput/high-content phenotyping and atlas building for model organisms demonstrate the importance of bioimage informatics. The essential techniques to the success of these applications, such as bioimage feature identification, segmentation and tracking, registration, annotation, mining, image data management and visualization, are further summarized, along with a brief overview of the available bioimage databases, analysis tools and other resources.
Indexed as
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.