ArticleNature communications2020
Phase imaging with computational specificity (PICS) for measuring dry mass changes in sub-cellular compartments.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers.
What it found
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Who cites it
73 citing papers in PubMed, 160 citations in OpenAlex.
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- Cell context-dependent in silico organelle localization in label-free microscopy images.Nature methods · 2026Article
- Plan meta-objective for sub-micron quantitative phase imaging.Light, science & applications · 2026Article
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- Near-zero photon bioimaging by fusing deep learning and ultralow-light microscopy.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Deciphering structural complexity of brain, joint, and muscle tissues using Fourier Ptychographic Scattered Light Microscopy.bioRxiv : the preprint server for biology · 2025Article
- Measuring Molecular Mass Densities at Subcellular Resolution Using Optical Diffraction Tomography.Methods in molecular biology (Clifton, N.J.) · 2025Article
- AI-driven strategies for advancing corneal cell therapy: a promising frontier.Frontiers in medicine · 2025Review
- Biomaterials for Cell Manufacturing.ACS macro letters · 2024Article
- Mantis: High-throughput 4D imaging and analysis of the molecular and physical architecture of cells.PNAS nexus · 2024Article
- A systematic evaluation of computational methods for cell segmentation.bioRxiv : the preprint server for biology · 2024Article
- GAN-based quantitative oblique back-illumination microscopy enables computationally efficient epi-mode refractive index tomography.Biomedical optics express · 2024Article
- Information-Distilled Generative Label-Free Morphological Profiling Encodes Cellular Heterogeneity.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- A systematic evaluation of computational methods for cell segmentation.Briefings in bioinformatics · 2024Article
13 more citing papers are in PubMed but not listed here.
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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
Due to its specificity, fluorescence microscopy has become a quintessential imaging tool in cell biology. However, photobleaching, phototoxicity, and related artifacts continue to limit fluorescence microscopy's utility. Recently, it has been shown that artificial intelligence (AI) can transform one form of contrast into another. We present phase imaging with computational specificity (PICS), a combination of quantitative phase imaging and AI, which provides information about unlabeled live cells with high specificity. Our imaging system allows for automatic training, while inference is built into the acquisition software and runs in real-time. Applying the computed fluorescence maps back to the quantitative phase imaging (QPI) data, we measured the growth of both nuclei and cytoplasm independently, over many days, without loss of viability. Using a QPI method that suppresses multiple scattering, we measured the dry mass content of individual cell nuclei within spheroids. In its current implementation, PICS offers a versatile quantitative technique for continuous simultaneous monitoring of individual cellular components in biological applications where long-term label-free imaging is desirable.
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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.