ArticlePhotoacoustics2022
Deep learning enables ultraviolet photoacoustic microscopy based histological imaging with near real-time virtual staining.
Article in Photoacoustics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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39 citing papers in PubMed, 80 citations in OpenAlex.
- Label-free ultraviolet photoacoustic microscopy for multiscale structural phenotyping of epithelial morphogenesis in organoid-derived intestinal epithelial wrinkle tissue.Photoacoustics · 2026Article
- Hardware-Attentive Programmable Fourier Ptychography Enables Task-Adaptive Label-Free Virtual Staining.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Paired CycleGAN-based virtual staining for 3D X-ray histology of bone-implant systems.Journal of synchrotron radiation · 2026Article
- Dual-Modal Autofluorescence Microscopy for CycleGAN-Based H&E-like Image Generation in Liver Tissue: A Preliminary Proof-of-Concept Study.Diagnostics (Basel, Switzerland) · 2026Article
- Ultraviolet Sensing-Guided Biomedical Systems: From Label-Free Imaging to Dosimetry and Therapy Feedback.Biosensors · 2026Review
- Photon absorption remote sensing (PARS): comprehensive absorption imaging enabling label-free biomolecule characterization and mapping.Scientific reports · 2026Article
- Label-free pathological subtyping of non-small cell lung cancer using deep classification and virtual immunohistochemical staining.NPJ digital medicine · 2026Article
- Label-free whole slide virtual multi-staining using dual-excitation photon absorption remote sensing microscopy.Npj imaging · 2026Article
- Deep Learning-Enabled Virtual Multiplexed Immunostaining of Label-Free Tissue for Vascular Invasion Assessment.BME frontiers · 2026Article
- Raman spectral band imaging for the diagnostics and classification of canine and feline cutaneous tumors.The veterinary quarterly · 2025Article
- AI-based pathomics in kidney diseases: progress and application.Renal failure · 2025Review
- 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 histopathological diagnosis of frozen sections based on multi-excitation and broad-emission autofluorescence imaging.Biomedical optics express · 2025Article
- A comprehensive review of high-performance photoacoustic microscopy systems.Photoacoustics · 2025Review
- Recent advancements in molecular photoacoustic tomography.JPhys photonics · 2025Review
- Mass spectrometric imaging of organic and metallic metabolites by plasmon-induced interfacial charge-transfer transition (PICTT) on Au sputtered ITO slides.Chemical science · 2025Article
- InterpolAI: deep learning-based optical flow interpolation and restoration of biomedical images for improved 3D tissue mapping.Nature methods · 2025Article
- A joint photoacoustic imaging and broadband spectral analysis for early-stage intraoperative pathology assessment: A case study with colorectal cancer.Photoacoustics · 2025Article
- Enhancing the pathological diagnosis of oral cancers using broadband ultraviolet photoacoustic microscopy.Biomedical optics express · 2025Article
- Label-free optical microscopy with artificial intelligence: a new paradigm in pathology.Biophotonics discovery · 2025Review
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Authors and funding
4 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Histological images can reveal rich cellular information of tissue sections, which are widely used by pathologists in disease diagnosis. However, the gold standard for histopathological examination is based on thin sections on slides, which involves inevitable time-consuming and labor-intensive tissue processing steps, hindering the possibility of intraoperative pathological assessment of the precious patient specimens. Here, by incorporating ultraviolet photoacoustic microscopy (UV-PAM) with deep learning, we show a rapid and label-free histological imaging method that can generate virtually stained histological images (termed Deep-PAM) for both thin sections and thick fresh tissue specimens. With the tissue non-destructive nature of UV-PAM, the imaged intact specimens can be reused for other ancillary tests. We demonstrated Deep-PAM on various tissue preparation protocols, including formalin-fixation and paraffin-embedding sections (7-µm thick) and frozen sections (7-µm thick) in traditional histology, and rapid assessment of intact fresh tissue (~ 2-mm thick, within 15 min for a tissue with a surface area of 5 mm × 5 mm). Deep-PAM potentially serves as a comprehensive histological imaging method that can be simultaneously applied in preoperative, intraoperative, and postoperative disease diagnosis.
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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.