Imaging of in vitro chicken leg using time-resolved near-infrared optical tomography

CGAN-rIRN: a data-augmented deep learning approach to accurate classification of mental tasks for a fNIRS-based brain-computer interface

Functional near-infrared spectroscopy (fNIRS) is increasingly used to investigate different mental tasks for brain-computer interface (BCI) control due to its excellent environmental and motion robustness. Feature extraction and classification strategy for fNIRS signal are essential to enhance the classification accuracy of voluntarily controlled BCI systems. The limitation of traditional machine learning classifiers (MLCs) lies in manual feature engineering, which is considered as one of the drawbacks that reduce accuracy. Since the fNIRS signal is a typical multivariate time series with multi-dimensionality and complexity, it makes the deep learning classifier (DLC) ideal for classifying neural activation patterns. However, the inherent bottleneck of DLCs is the requirement of substantial-scale, high-quality labeled training data and expensive computational resources to train deep networks. The existing DLCs for classifying mental tasks do not fully consider the temporal and spatial properties of fNIRS signals. Therefore, a specifically-designed DLC is desired to classify multi-tasks with high accuracy in fNIRS-BCI. To this end, we herein propose a novel data-augmented DLC to accurately classify mental tasks, which employs a convolution-based conditional generative adversarial network (CGAN) for data augmentation and a revised Inception-ResNet (rIRN) based DLC. The CGAN is utilized to generate class-specific synthetic fNIRS signals to augment the training dataset. The network architecture of rIRN is elaborately designed in accordance with the characteristics of the fNIRS signal, with serial multiple spatial and temporal feature extraction modules (FEMs), where each FEM performs deep and multi-scale feature extraction and fusion. The results of the paradigm experiments show that the proposed CGAN-rIRN approach improves the single-trial accuracy for mental arithmetic and mental singing tasks in both the data augmentation and classifier, as compared to the traditional MLCs and the commonly used DLCs. The proposed fully data-driven hybrid deep learning approach paves a promising way to improve the classification performance of volitional control fNIRS-BCI.

Time-Domain Near-Infrared Spectroscopy and Imaging: A Review

This article reviews the past and current statuses of time-domain near-infrared spectroscopy (TD-NIRS) and imaging. Although time-domain technology is not yet widely employed due to its drawbacks of being cumbersome, bulky, and very expensive compared to commercial continuous wave (CW) and frequency-domain (FD) fNIRS systems, TD-NIRS has great advantages over CW and FD systems because time-resolved data measured by TD systems contain the richest information about optical properties inside measured objects. This article focuses on reviewing the theoretical background, advanced theories and methods, instruments, and studies on clinical applications for TD-NIRS including some clinical studies which used TD-NIRS systems. Major events in the development of TD-NIRS and imaging are identified and summarized in chronological tables and figures. Finally, prospects for TD-NIRS in the near future are briefly described.

Review of structured light in diffuse optical imaging

Diffuse optical imaging probes deep living tissue enabling structural, functional, metabolic, and molecular imaging. Recently, due to the availability of spatial light modulators, wide-field quantitative diffuse optical techniques have been implemented, which benefit greatly from structured light methodologies. Such implementations facilitate the quantification and characterization of depth-resolved optical and physiological properties of thick and deep tissue at fast acquisition speeds. We summarize the current state of work and applications in the three main techniques leveraging structured light: spatial frequency-domain imaging, optical tomography, and single-pixel imaging. The theory, measurement, and analysis of spatial frequency-domain imaging are described. Then, advanced theories, processing, and imaging systems are summarized. Preclinical and clinical applications on physiological measurements for guidance and diagnosis are summarized. General theory and method development of tomographic approaches as well as applications including fluorescence molecular tomography are introduced. Lastly, recent developments of single-pixel imaging methodologies and applications are reviewed.

Non-tissue-like features in the time-of-flight distributions of plastic tissue phantoms

We measure high-temporal-resolution time-of-flight distributions of picosecond laser pulses in the visible and near-infrared, scattered in the forward direction by solid and liquid phantoms, and compare them to those obtained by using ex vivo tissues. We demonstrate that time-of-flight distributions from solid phantoms made of Delrin, Nylon, and Teflon are modulated by ripples that are absent in the biological samples and disappear when the temporal and/or angular resolution of the measuring apparatus is decreased. This behavior prevents the use of such materials as tissue phantoms when spatial mode and time selection are required, such as in imaging methods exploiting early arriving photons.

Time-resolved diffuse optical tomography and its application to in vitro and in vivo imaging

This work reviews our research during the past several years on time-resolved (TR) near-infrared diffuse optical tomography (DOT). Following an introduction of the measuring modes, two proposed schemes of image reconstruction in TR-DOT are described: one utilizes the full TR data, and the other, referred to as the modified generalized pulse spectrum technique (GPST), uses the featured data extracted from the TR measurement. The performances of the two algorithms in quantitativeness and spatial resolution are comparatively investigated with 2-D simulated data. TR-DOT images are then presented for phantom experiments, which are obtained by using a 16-channel time-correlated single photon counting system, and the factors affecting the quantification of the reconstruction are discussed. Finally, in vitro and in vivo imaging examples are illustrated for validating the capibility of TR-DOT to provide not only the anatomical but also the physiological information of the objects.

Light diffusion model for determination of optical properties of rectangular parallelepiped highly scattering media

A method to determine the absorption and reduced scattering coefficients of rectangular parallelepiped highly scattering media from frequency-domain photon migration measurements is presented. An analytical model for photon diffusion propagation in the rectangular parallelepiped media is established using the method of images and extrapolated boundary conditions. This present technique has simplicity, accuracy, and rapid computability as compared with the Monte Carlo or finite element methods. The theoretical predictions are verified with experimental measurements using a white polyacetal resin, and the errors introduced by using the slab geometry for the optical property determination are identified.

Time-resolved diffuse optical tomographic imaging for the provision of both anatomical and functional information about biological tissue

We present in vivo images of near-infrared (NIR) diffuse optical tomography (DOT) of human lower legs and forearm to validate the dual functions of a time-resolved (TR) NIR DOT in clinical diagnosis, i.e., to provide anatomical and functional information simultaneously. The NIR DOT system is composed of time-correlated single-photon-counting channels, and the image reconstruction algorithm is based on the modified generalized pulsed spectral technique, which effectively incorporates the TR data with reasonable computation time. The reconstructed scattering images of both the lower legs and the forearm revealed their anatomies, in which the bones were clearly distinguished from the muscles. In the absorption images, some of the blood vessels were observable. In the functional imaging, a subject was requested to do handgripping exercise to stimulate physiological changes in the forearm tissue. The images of oxyhemoglobin, deoxyhemoglobin, and total hemoglobin concentration changes in the forearm were obtained from the differential images of the absorption at three wavelengths between the exercise and the rest states, which were reconstructed with a differential imaging scheme. These images showed increases in both blood volume and oxyhemoglobin concentration in the arteries and simultaneously showed hypoxia in the corresponding muscles. All the results have demonstrated the capability of TR NIR DOT by reconstruction of the absolute images of the scattering and the absorption with a high spatial resolution that finally provided both the anatomical and functional information inside bulky biological tissues.

Simple peak shift analysis of time-of-flight data with a slow instrumental response function

Analysis of time-of-flight (TOF) data is sometimes limited by the instrumental response function, and optical parameters are extracted from the observed response curve by several mathematical methods, such as deconvolution. In contrast to this, we demonstrate that a method using shifts of the peak time of the response curve with different source-detector separations can yield the average path length of the light traveling in a tissue-like sample without deconvolution. In addition, combining the intensity information allows us to separate the scattering and absorption coefficients. This simple method is more robust in signal-to-noise ratio than the moment analysis, which also does not require the deconvolution procedure, because the peak position is not significantly dependent on the baseline fluctuation and the contamination of the scattering. The analysis is demonstrated by TOF measurements of an Intralipid solution at 800 nm, and is applied to the measurements at 1.29 microm, where the temporal response of photomultiplier tubes is not sufficiently good.