ReviewNature methods2023
Artificial intelligence-enabled quantitative phase imaging methods for life sciences.
Review in Nature methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
What it found
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Who cites it
46 citing papers in PubMed.
- Hybrid deep reconstruction for vignetting-free upconversion imaging through scattering in epsilon-near-zero materials.Light, science & applications · 2026Article
- Structural, Compositional, and Dielectric State Profiling in Label-Free Single-Cell Monitoring.Small methods · 2026Review
- Intelligent Stain-Free Histology on Structural Colorimetric Nanocavities.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Cell-MICS: Detecting Immune Cells With Label-Free Two-Photon Autofluorescence and Deep Learning.Journal of biophotonics · 2026Article
- Label-free detection of ovarian cancer cells in ascites-related cell models using digital holographic flow cytometry.Biomedical optics express · 2026Article
- Virtual histology imaging of lymph nodesCancer biology & medicine · 2026Observational
- Single capture quantitative oblique back-illumination microscopy.Npj imaging · 2026Article
- Label-free correlative morpho-chemical tomography of 3D kidney mesangial cells.Journal of biomedical optics · 2026Article
- Neural phase microscopy with metasurface optics for real-time and nanoscale quantitative phase imaging.Nature communications · 2026Article
- Article
- Gradient Descent to Predict Enzyme Inhibition.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Gold-Doped Hybrid Nanoparticles: A Versatile Tool for Multimodal Imaging of Cell Trafficking.Pharmaceutics · 2025Article
- Fourier ptychographic enhancement of iterative pathways: autonomous 3D momentum coordination in hybrid ML-PIE architectures.Biomedical optics express · 2025Article
- Lightweight CNN efficiently discriminates ovarian cancer cells from a tumor microenvironment via holographic imaging flow cytometry.Biomedical optics express · 2025Article
- Innovations in assisted reproductive technology through the advances in artificial intelligence and image processing.Obstetrics & gynecology science · 2025Review
- Differential Phase Contrast Imaging to Predict MSC Immune Function.Advanced healthcare materials · 2025Article
- A correlative quantitative phase contrast and fluorescence super-resolution microscope for imaging molecules in their cellular context.bioRxiv : the preprint server for biology · 2025Article
- Determination of Drug Sensitivity in Patient Derived Models of Breast Cancer by Multiparametric QPI.bioRxiv : the preprint server for biology · 2025Article
- Structural Engineering of Layered Nanomaterials for Biomedical Applications.Chemical reviews · 2025Review
- Investigation of Viscoelastic Properties of Macrophage Membrane-Cytoskeleton Induced by Gold Nanorods in Leishmania Infection.Nanomaterials (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
16 authors.
Funding
Abstract
Quantitative phase imaging, integrated with artificial intelligence, allows for the rapid and label-free investigation of the physiology and pathology of biological systems. This review presents the principles of various two-dimensional and three-dimensional label-free phase imaging techniques that exploit refractive index as an intrinsic optical imaging contrast. In particular, we discuss artificial intelligence-based analysis methodologies for biomedical studies including image enhancement, segmentation of cellular or subcellular structures, classification of types of biological samples and image translation to furnish subcellular and histochemical information from label-free phase images. We also discuss the advantages and challenges of artificial intelligence-enabled quantitative phase imaging analyses, summarize recent notable applications in the life sciences, and cover the potential of this field for basic and industrial research in the life sciences.
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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.