ArticleBiomedical optics express2020
High compression deep learning based single-pixel hyperspectral macroscopic fluorescence lifetime imaging
Article in Biomedical optics express, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed.
- Fluorescence Lifetime Imaging for Quantification of Targeted Drug Delivery in Varying Tumor Microenvironments.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Overcoming photon and spatiotemporal sparsity in fluorescence lifetime imaging with SparseFLIM.Communications biology · 2024Article
- Advancements in fluorescence lifetime imaging microscopy Instrumentation: Towards high speed and 3D.Current opinion in solid state & materials science · 2024Article
- Applications of machine learning in time-domain fluorescence lifetime imaging: a review.Methods and applications in fluorescence · 2024Review
- Computational macroscopic lifetime imaging and concentration unmixing of autofluorescence.Journal of biophotonics · 2022Article
- Suppression of natural lens fluorescence in fundus autofluorescence measurements: review of hardware solutions.Biomedical optics express · 2022Review
- Live-cell fluorescence spectral imaging as a data science challenge.Biophysical reviews · 2022Review
- 3D k-space reflectance fluorescence tomography via deep learning.Optics letters · 2022Article
- Deep learning in macroscopic diffuse optical imaging.Journal of biomedical optics · 2022Review
- Deep Learning in Biomedical Optics.Lasers in surgery and medicine · 2021Review
- Recent innovations in fluorescence lifetime imaging microscopy for biology and medicine.Journal of biomedical optics · 2021Article
- Luminescence lifetime imaging of three-dimensional biological objects.Journal of cell science · 2021Article
- Macroscopic fluorescence lifetime topography enhanced via spatial frequency domain imaging.Optics letters · 2020Article
- UNMIX-ME: spectral and lifetime fluorescence unmixing via deep learning.Biomedical optics express · 2020Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Single pixel imaging frameworks facilitate the acquisition of high-dimensional optical data in biological applications with photon starved conditions. However, they are still limited to slow acquisition times and low pixel resolution. Herein, we propose a convolutional neural network for fluorescence lifetime imaging with compressed sensing at high compression (NetFLICS-CR), which enables in vivo applications at enhanced resolution, acquisition and processing speeds, without the need for experimental training datasets. NetFLICS-CR produces intensity and lifetime reconstructions at 128 × 128 pixel resolution over 16 spectral channels while using only up to 1% of the required measurements, therefore reducing acquisition times from ∼2.5 hours at 50% compression to ∼3 minutes at 99% compression. Its potential is demonstrated in silico, in vitro and for mice in vivo through the monitoring of receptor-ligand interactions in liver and bladder and further imaging of intracellular delivery of the clinical drug Trastuzumab to HER2-positive breast tumor xenografts. The data acquisition time and resolution improvement through NetFLICS-CR, facilitate the translation of single pixel macroscopic flurorescence lifetime imaging (SP-MFLI) for in vivo monitoring of lifetime properties and drug uptake.
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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.