ArticleJournal of biomedical optics2020
Real-time video-rate perfusion imaging using multi-exposure laser speckle contrast imaging and machine learning.
Article in Journal of biomedical optics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06009939 (Microvascular Sex and Age-related Day-to-day Variability in Healthy Subjects), which is not on this map. Cited by 8 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Microvascular Sex and Age-related Day-to-day Variability in Healthy Subjects
Who cites it
8 citing papers in PubMed.
- Noninvasive Bedside Approaches for Assessing Microvascular Dysfunction.Journal of vascular research · 2025Review
- Quantum machine learning enhanced laser speckle analysis for precise speed prediction.Scientific reports · 2024Article
- Multiexposure laser speckle contrast analysis system calibration limited by perfusion-dependent scattering on the skin.Journal of biomedical optics · 2023Article
- Quasi-analytic solution for real-time multi-exposure speckle imaging of tissue perfusion.Biomedical optics express · 2023Article
- A quasi-analytic solution for real-time multi-exposure speckle imaging of tissue perfusion.bioRxiv : the preprint server for biology · 2023Article
- Prediction of motion artifacts caused by translation in handheld laser speckle contrast imaging.Journal of biomedical optics · 2023Article
- Speed-resolved perfusion imaging using multi-exposure laser speckle contrast imaging and machine learning.Journal of biomedical optics · 2023Article
- Laser Doppler Spectrum Analysis Based on Calculation of Cumulative Sums Detects Changes in Skin Capillary Blood Flow in Type 2 Diabetes Melitus.Diagnostics (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
significanceMulti-exposure laser speckle contrast imaging (MELSCI) estimates microcirculatory blood perfusion more accurately than single-exposure LSCI. However, the technique has been hampered by technical limitations due to massive data throughput requirements and nonlinear inverse search algorithms, limiting it to an offline technique where data must be postprocessed.
aimTo present an MELSCI system capable of continuous acquisition and processing of MELSCI data, enabling real-time video-rate perfusion imaging with high accuracy. APPROACH: The MELSCI algorithm was implemented in programmable hardware (field programmable gate array) closely interfaced to a high-speed CMOS sensor for real-time calculation. Perfusion images were estimated in real-time from the MELSCI data using an artificial neural network trained on simulated data. The MELSCI perfusion was compared to two existing single-exposure metrics both quantitatively in a controlled phantom experiment and qualitatively in vivo.
resultsThe MELSCI perfusion shows higher signal dynamics compared to both single-exposure metrics, both spatially and temporally where heartbeat-related variations are resolved in much greater detail. The MELSCI perfusion is less susceptible to measurement noise and is more linear with respect to laser Doppler perfusion in the phantom experiment (R2 = 0.992).
conclusionsThe presented MELSCI system allows for real-time acquisition and calculation of high-quality perfusion at 15.6 frames per second.
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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.