ArticleJournal of biomedical optics2020
Machine learning for direct oxygen saturation and hemoglobin concentration assessment using diffuse reflectance spectroscopy.
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. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- MLDT: an open-source multilayer diffusion theory Python implementation.Journal of biomedical optics · 2026Article
- Learning to simulate realistic human diffuse reflectance spectra.Journal of biomedical optics · 2026Article
- Propagation of Laguerre-Gaussian beam intensities through optically thick turbid media.Scientific reports · 2025Article
- Robust estimation of skin physiological parameters from hyperspectral images using Bayesian neural networks.Journal of biomedical optics · 2025Article
- Learnable real-time inference of molecular composition from diffuse spectroscopy of brain tissue.Journal of biomedical optics · 2024Article
- Hyperspectral imaging with deep learning for quantification of tissue hemoglobin, melanin, and scattering.Journal of biomedical optics · 2024Article
- Devices and Methods for Dosimetry of Personalized Photodynamic Therapy of Tumors: A Review on Recent Trends.Cancers · 2024Review
- Artificial neural networks trained on simulated multispectral data for real-time imaging of skin microcirculatory blood oxygen saturation.Journal of biomedical optics · 2024Article
- Designing a use-error robust machine learning model for quantitative analysis of diffuse reflectance spectra.Journal of biomedical optics · 2024Article
- Neural network-based inverse model for diffuse reflectance spectroscopy.Biomedical optics express · 2023Article
- Machine Learning Diffuse Optical Tomography Using Extreme Gradient Boosting and Genetic Programming.Bioengineering (Basel, Switzerland) · 2023Article
- Speed-resolved perfusion imaging using multi-exposure laser speckle contrast imaging and machine learning.Journal of biomedical optics · 2023Article
- VIS-NIR Diffuse Reflectance Spectroscopy System with Self-Calibrating Fiber-Optic Probe: Study of Perturbation Resistance.Diagnostics (Basel, Switzerland) · 2023Article
- Performance estimation of optical skin probe in short wavelength infrared spectroscopy based on Monte-Carlo simulation.Scientific reports · 2022Article
- Applications of Neural Networks in Biomedical Data Analysis.Biomedicines · 2022Review
- Laser Doppler Flowmetry Combined with Spectroscopy to Determine Peripheral Tissue Perfusion and Oxygen Saturation: A Pilot Study in Healthy Volunteers and Patients with Peripheral Arterial Disease.Journal of personalized medicine · 2022Article
- Regression-based neural network for improving image reconstruction in diffuse optical tomography.Biomedical optics express · 2022Article
- Multispectral snapshot imaging of skin microcirculatory hemoglobin oxygen saturation using artificial neural networks trained on in vivo data.Journal of biomedical optics · 2022Article
- Vasomotion analysis of speed resolved perfusion, oxygen saturation, red blood cell tissue fraction, and vessel diameter: Novel microvascular perspectives.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2022Article
- Optical property recovery with spatially-resolved diffuse reflectance at short source-detector separations using a compact fiber-optic probe.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
significanceDiffuse reflectance spectroscopy (DRS) is frequently used to assess oxygen saturation and hemoglobin concentration in living tissue. Methods solving the inverse problem may include time-consuming nonlinear optimization or artificial neural networks (ANN) determining the absorption coefficient one wavelength at a time.
aimTo present an ANN-based method that directly outputs the oxygen saturation and the hemoglobin concentration using the shape of the measured spectra as input. APPROACH: A probe-based DRS setup with dual source-detector separations in the visible wavelength range was used. ANNs were trained on spectra generated from a three-layer tissue model with oxygen saturation and hemoglobin concentration as target.
resultsModeled evaluation data with realistic measurement noise showed an absolute root-mean-square (RMS) deviation of 5.1% units for oxygen saturation estimation. The relative RMS deviation for hemoglobin concentration was 13%. This accuracy is at least twice as good as our previous nonlinear optimization method. On blood-intralipid phantoms, the RMS deviation from the oxygen saturation derived from partial oxygen pressure measurements was 5.3% and 1.6% in two separate measurement series. Results during brachial occlusion showed expected patterns.
conclusionsThe presented method, directly assessing oxygen saturation and hemoglobin concentration, is fast, accurate, and robust to noise.
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