ArticleBiomedical optics express2020
Deep learning model for ultrafast quantification of blood flow in diffuse correlation spectroscopy.
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 13 papers.
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Who cites it
13 citing papers in PubMed.
- Assessing liquid light guides in diffuse correlation spectroscopy systems.Biomedical optics express · 2025Article
- Comparison of diffuse correlation spectroscopy analytical models for cerebral blood flow measurements.Journal of biomedical optics · 2025Article
- Cerebral blood flow monitoring using a deep learning implementation of the two-layer diffuse correlation spectroscopy analytical model with a 512 × 512 SPAD array.Neurophotonics · 2025Article
- From Neural Networks to Transformers: Achieving High and Fast Precision in Fluorescence Correlation Spectroscopy Analysis.ACS omega · 2025Article
- Fast blood flow index reconstruction of diffuse correlation spectroscopy using a back-propagation-free data-driven algorithm.Biomedical optics express · 2025Article
- A Device-on-Chip Solution for Real-Time Diffuse Correlation Spectroscopy Using FPGA.Biosensors · 2024Article
- Quantification of blood flow index in diffuse correlation spectroscopy using a robust deep learning method.Journal of biomedical optics · 2024Article
- Diffuse Correlation Spectroscopy: A Review of Recent Advances in Parallelisation and Depth Discrimination Techniques.Sensors (Basel, Switzerland) · 2023Review
- Deep-learning-based separation of shallow and deep layer blood flow rates in diffuse correlation spectroscopy.Biomedical optics express · 2023Article
- Current capabilities and future perspectives of FCS: super-resolution microscopy, machine learning, and in vivo applications.Communications biology · 2023Review
- Performance optimisation of a holographic Fourier domain diffuse correlation spectroscopy instrument.Biomedical optics express · 2022Article
- Deep Learning in Biomedical Optics.Lasers in surgery and medicine · 2021Review
- Quantification of blood flow index in diffuse correlation spectroscopy using long short-term memory architecture.Biomedical optics express · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diffuse correlation spectroscopy (DCS) is increasingly used in the optical imaging field to assess blood flow in humans due to its non-invasive, real-time characteristics and its ability to provide label-free, bedside monitoring of blood flow changes. Previous DCS studies have utilized a traditional curve fitting of the analytical or Monte Carlo models to extract the blood flow changes, which are computationally demanding and less accurate when the signal to noise ratio decreases. Here, we present a deep learning model that eliminates this bottleneck by solving the inverse problem more than 2300% faster, with equivalent or improved accuracy compared to the nonlinear fitting with an analytical method. The proposed deep learning inverse model will enable real-time and accurate tissue blood flow quantification with the DCS technique.
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Registered trials
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