ArticleScientific reports2021
Machine learning estimation of tissue optical properties.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Multi-layer self-calibrated algorithm for transabdominal fetal pulse oximetry: simulation andJPhys photonics · 2026Article
- Photobiomodulation for skeletal muscle regeneration: mechanisms, dosimetry, and translational challenges.Frontiers in bioengineering and biotechnology · 2026Review
- Analysis of the experimental absorption spectrum of the rabbit lung and identification of its components.Journal of biophotonics · 2025Article
- Structured light imaging mesoscopy: detection of embedded morphological changes in superficial tissues.Journal of biomedical optics · 2025Article
- Automated spectral decomposition and reconstruction of optical properties using a mixed autoencoder approach.Journal of biomedical optics · 2025Article
- Effects of cold storage on double integrating sphere optical property measurements of porcine dermis and subcutaneous fat from 400 to 1100 nm.Journal of biomedical optics · 2025Article
- Learnable real-time inference of molecular composition from diffuse spectroscopy of brain tissue.Journal of biomedical optics · 2024Article
- Reconstruction of Optical Properties in Turbid Media: Omitting the Need of the Collimated Transmission for an Integrating Sphere Setup.Sensors (Basel, Switzerland) · 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
- Physics-guided neural network for tissue optical properties estimation.Biomedical optics express · 2023Article
- Real-time and accurate estimationBiomedical optics express · 2023Article
- Machine Learning Diffuse Optical Tomography Using Extreme Gradient Boosting and Genetic Programming.Bioengineering (Basel, Switzerland) · 2023Article
- Coronary artery properties in atherosclerosis: A deep learning predictive model.Frontiers in physiology · 2023Article
- Efficient computation of the steady-state and time-domain solutions of the photon diffusion equation in layered turbid media.Scientific reports · 2022Article
- MCDataset: a public reference dataset of Monte Carlo simulated quantities for multilayered and voxelated tissues computed by massively parallel PyXOpto Python package.Journal of biomedical optics · 2022Article
- Phase function estimation from a diffuse optical image via deep learning.Physics in medicine and biology · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Dynamic, in vivo measurement of the optical properties of biological tissues is still an elusive and critically important problem. Here we develop a technique for inverting a Monte Carlo simulation to extract tissue optical properties from the statistical moments of the spatio-temporal response of the tissue by training a 5-layer fully connected neural network. We demonstrate the accuracy of the method across a very wide parameter space on a single homogeneous layer tissue model and demonstrate that the method is insensitive to parameter selection of the neural network model itself. Finally, we propose an experimental setup capable of measuring the required information in real time in an in vivo environment and demonstrate proof-of-concept level experimental results.
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