ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2022
High-Throughput, Label-Free and Slide-Free Histological Imaging by Computational Microscopy and Unsupervised Learning.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
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The trial behind it
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Who cites it
21 citing papers in PubMed.
- Generative AI for misalignment-resistant virtual staining to accelerate histopathology workflows.Nature communications · 2026Article
- Real-Time High-Definition Hyperspectral Endoscopy via Spatial-Temporal Low-Frequency-Stochastic Spectral Encoding.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Rapid Arbitrary-Shape Microscopy of Unsectioned Tissues for Precise Intraoperative Tumor Margin Assessment.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Deep UV laser scanning microscopy with integrated 1050 nm spectral-domain optical coherence tomography for multi-contrast tissue imaging.Biomedical optics express · 2025Article
- Label-free optical microscopy with artificial intelligence: a new paradigm in pathology.Biophotonics discovery · 2025Review
- Exploring Multiplex Immunohistochemistry (mIHC) Techniques and Histopathology Image Analysis: Current Practice and Potential for Clinical Incorporation.Cancer medicine · 2025Review
- Accurate attenuation characterization in optical coherence tomography using multi-reference phantoms and deep learning.Biomedical optics express · 2024Article
- Metabolic light absorption, scattering, and emission (MetaLASE) microscopy.Science advances · 2024Article
- Rapid full-color serial sectioning tomography with speckle illumination and ultraviolet excitation.Npj imaging · 2024Article
- Information-Distilled Generative Label-Free Morphological Profiling Encodes Cellular Heterogeneity.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Deep learning-assisted low-cost autofluorescence microscopy for rapid slide-free imaging with virtual histological staining.Biomedical optics express · 2024Article
- Exceeding the limit for microscopic image translation with a deep learning-based unified framework.PNAS nexus · 2024Article
- Noninvasive Nonlinear Optical Computational Histology.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Harnessing the power of optical microscopy for visualization and analysis of histopathological images.Biomedical optics express · 2023Review
- Deep learning-enabled realistic virtual histology with ultraviolet photoacoustic remote sensing microscopy.Nature communications · 2023Article
- Ultraviolet metasurface-assisted photoacoustic microscopy with great enhancement in DOF for fast histology imaging.Photoacoustics · 2023Article
- Rapid and label-free histological imaging of unprocessed surgical tissues via dark-field reflectance ultraviolet microscopy.iScience · 2023Article
- Imaging peripheral nerve micro-anatomy with MUSE, 2D and 3D approaches.Scientific reports · 2022Article
- Three-dimensional label-free histological imaging of whole organs by microtomy-assisted autofluorescence tomography.iScience · 2022Article
- Unsupervised Hyperspectral Microscopic Image Segmentation Using Deep Embedded Clustering Algorithm.Scanning · 2022Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Rapid and high-resolution histological imaging with minimal tissue preparation has long been a challenging and yet captivating medical pursuit. Here, the authors propose a promising and transformative histological imaging method, termed computational high-throughput autofluorescence microscopy by pattern illumination (CHAMP). With the assistance of computational microscopy, CHAMP enables high-throughput and label-free imaging of thick and unprocessed tissues with large surface irregularity at an acquisition speed of 10 mm
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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.