ArticleJournal of microscopy2014
Pipeline for illumination correction of images for high-throughput microscopy.
Article in Journal of microscopy, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.
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Who cites it
49 citing papers in PubMed.
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- Brieflow: an integrated computational pipeline for high-throughput analysis of optical pooled screening data.Nature communications · 2026Article
- Progress and new challenges in image-based profiling.Molecular systems biology · 2026Review
- Unlocking the potential of computational phenotypic drug discovery: methods, challenges, and future directions.NPJ systems biology and applications · 2026Review
- Analyzing Cell Painting PLUS Data Using Cell Profiler and KNIME Analytics Platform.Methods in molecular biology (Clifton, N.J.) · 2026Article
- A pooled Cell Painting CRISPR screening platform enables de novo inference of gene function by self-supervised deep learning.Nature communications · 2025Article
- Confounder-aware foundation modeling for accurate phenotype profiling in cell imaging.Npj imaging · 2025Article
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- Morphological map of under- and overexpression of genes in human cells.Nature methods · 2025Article
- Automated Segmentation and Morphometric Analysis of Thioflavin-S-Stained Amyloid Deposits in Alzheimer's Disease Brains and Age-Matched Controls Using Weakly Supervised Deep Learning.International journal of molecular sciences · 2025Article
- A morphology and secretome map of pyroptosis.Molecular biology of the cell · 2025Article
- High-content microscopy and machine learning characterize a cell morphology signature ofbioRxiv : the preprint server for biology · 2025Article
- Predicting cell morphological responses to perturbations using generative modeling.Nature communications · 2025Article
- Evaluation of image analysis tools for the measurement of cellular morphology.Frontiers in cell and developmental biology · 2025Review
- SPACe: an open-source, single-cell analysis of Cell Painting data.Nature communications · 2024Article
- Three million images and morphological profiles of cells treated with matched chemical and genetic perturbations.Nature methods · 2024Article
- Morphological profiling for drug discovery in the era of deep learning.Briefings in bioinformatics · 2024Review
- Learning representations for image-based profiling of perturbations.Nature communications · 2024Article
- Microsnoop: A generalist tool for microscopy image representation.Innovation (Cambridge (Mass.)) · 2024Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The presence of systematic noise in images in high-throughput microscopy experiments can significantly impact the accuracy of downstream results. Among the most common sources of systematic noise is non-homogeneous illumination across the image field. This often adds an unacceptable level of noise, obscures true quantitative differences and precludes biological experiments that rely on accurate fluorescence intensity measurements. In this paper, we seek to quantify the improvement in the quality of high-content screen readouts due to software-based illumination correction. We present a straightforward illumination correction pipeline that has been used by our group across many experiments. We test the pipeline on real-world high-throughput image sets and evaluate the performance of the pipeline at two levels: (a) Z'-factor to evaluate the effect of the image correction on a univariate readout, representative of a typical high-content screen, and (b) classification accuracy on phenotypic signatures derived from the images, representative of an experiment involving more complex data mining. We find that applying the proposed post-hoc correction method improves performance in both experiments, even when illumination correction has already been applied using software associated with the instrument. To facilitate the ready application and future development of illumination correction methods, we have made our complete test data sets as well as open-source image analysis pipelines publicly available. This software-based solution has the potential to improve outcomes for a wide-variety of image-based HTS experiments.
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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.