ArticleNeurophotonics2023
Short-separation regression incorporated diffuse optical tomography image reconstruction modeling for high-density functional near-infrared spectroscopy.
Article in Neurophotonics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 16 citations in OpenAlex.
- Characterization of a fiber-coupled SPAD camera system for deep-tissue blood-flow measurement using diffuse correlation spectroscopy.Biomedical optics express · 2026Article
- Surface-based image reconstruction optimization for high-density functional near-infrared spectroscopy.Neurophotonics · 2026Article
- Quantifying the impact of hair and skin characteristics on fNIRS signal quality for enhanced inclusivity.Nature human behaviour · 2025Article
- Mapping human cerebral blood flow with high-density, multi-channel speckle contrast optical spectroscopy.Communications biology · 2025Article
- Aberrant neural activation during inhibitory control in girls with fragile X syndrome.Cerebral cortex (New York, N.Y. : 1991) · 2025Article
- High-density multidistance fNIRS enhances detection of brain activity during a word-color Stroop task.Neurophotonics · 2025Article
- Co-localized optode-electrode design for multimodal functional near infrared spectroscopy and electroencephalography.Neurophotonics · 2025Article
- Continuous Wave-Diffuse Optical Tomography (CW-DOT) in Human Brain Mapping: A Review.Sensors (Basel, Switzerland) · 2025Review
- Multimodal fNIRS-EEG sensor fusion: Review of data-driven methods and perspective for naturalistic brain imaging.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Quantifying the Impact of Hair and Skin Characteristics on Signal Quality with Practical Recommendations for Improvement.bioRxiv : the preprint server for biology · 2024Article
- ninjaNIRS: an open hardware solution for wearable whole-head high-density functional near-infrared spectroscopy.Biomedical optics express · 2024Article
- NiReject: toward automated bad channel detection in functional near-infrared spectroscopy.Neurophotonics · 2024Article
- scatterBrains: an open database of human head models and companion optode locations for realistic Monte Carlo photon simulations.Journal of biomedical optics · 2023Article
- Validation of the Linearity in Image Reconstruction Methods for Speckle Contrast Optical Tomography.IEEE journal of selected topics in quantum electronics : a publication of the IEEE Lasers and Electro-optics SocietyArticle
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Significance: Short-separation (SS) regression and diffuse optical tomography (DOT) image reconstruction, two widely adopted methods in functional near-infrared spectroscopy (fNIRS), were demonstrated to individually facilitate the separation of brain activation and physiological signals, with further improvement using both sequentially. We hypothesized that doing both simultaneously would further improve the performance. Aim: Motivated by the success of these two approaches, we propose a method, SS-DOT, which applies SS and DOT simultaneously. Approach: The method, which employs spatial and temporal basis functions to represent the hemoglobin concentration changes, enables us to incorporate SS regressors into the time series DOT model. To benchmark the performance of the SS-DOT model against conventional sequential models, we use fNIRS resting state data augmented with synthetic brain response as well as data acquired during a ball squeezing task. The conventional sequential models comprise performing SS regression and DOT. Results: The results show that the SS-DOT model improves the image quality by increasing the contrast-to-background ratio by a threefold improvement. The benefits are marginal at small brain activation. Conclusions: The SS-DOT model improves the fNIRS image reconstruction quality.
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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.