ArticleJournal of biomedical optics2022
Multispectral snapshot imaging of skin microcirculatory hemoglobin oxygen saturation using artificial neural networks trained on in vivo data.
Article in Journal of biomedical optics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 13 citations in OpenAlex.
- Learning to simulate realistic human diffuse reflectance spectra.Journal of biomedical optics · 2026Article
- Development and clinical validation of a clinically translatable non-chip-on-tip transvaginal imaging system (GynoSight v2.0) for early detection of premalignant cervical lesions.Journal of biomedical optics · 2025Article
- Machine learning in point-of-care testing: innovations, challenges, and opportunities.Nature communications · 2025Review
- Background Light Suppression for Multispectral Imaging in Surgical Settings.Sensors (Basel, Switzerland) · 2024Article
- Learnable real-time inference of molecular composition from diffuse spectroscopy of brain tissue.Journal of biomedical optics · 2024Article
- Artificial neural networks trained on simulated multispectral data for real-time imaging of skin microcirculatory blood oxygen saturation.Journal of biomedical optics · 2024Article
- Optimizing clinical OBiomedical optics express · 2024Article
- Multispectral indices for real-time and non-invasive tissue ischemia monitoring using snapshot cameras.Biomedical optics express · 2024Article
- Switchable LED-based laparoscopic multispectral system for rapid high-resolution perfusion imaging.Journal of biomedical optics · 2023Article
- Temporal Evaluation of the Surface Area of Treated Skin Ulcers Caused by Cutaneous Leishmaniasis and Relation with Optical Parameters in an Animal Model: A Proof of Concept.Sensors (Basel, Switzerland) · 2023Article
- A non-contact oxygen saturation detection method based on dynamic spectrum.Infrared physics & technology · 2022Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
significanceDeveloping algorithms for estimating blood oxygenation from snapshot multispectral imaging (MSI) data is challenging due to the complexity of sensor characteristics and photon transport modeling in tissue. We circumvent this using a method where artificial neural networks (ANNs) are trained on in vivo MSI data with target values from a point-measuring reference method.
aimTo develop and evaluate a methodology where a snapshot filter mosaic camera is utilized for imaging skin hemoglobin oxygen saturation (SO2), using ANNs. APPROACH: MSI data were acquired during occlusion provocations. ANNs were trained to estimate SO2 with MSI data as input, targeting data from a validated probe-based reference system. Performance of ANNs with different properties and training data sets was compared.
resultsThe method enables spatially resolved estimation of skin tissue SO2. Results are comparable to those acquired using a Monte-Carlo-based approach when relevant training data are used.
conclusionsTraining an ANN on in vivo MSI data covering a wide range of target values acquired during an occlusion protocol enable real-time estimation of SO2 maps. Data from the probe-based reference system can be used as target despite differences in sampling depth and measurement position.
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