The study of photon propagation in highly scattering media (diffuse optics) is a powerful tool to noninvasively investigate biological tissues in depth.^1,2 For most biological media in the 600- to 1100-nm range, the scattering coefficient is much higher than the absorption coefficient, thus hindering information from the human body that in absence of scattering would appear transparent as a feebly colored glass. The attractiveness of probing the human tissues and their functions with light has fostered great efforts to cope with the challenges of “diffuse optics,” leading to a whole range of new physical concepts, theoretical models, instruments, measurement approaches, and applications. The terms near-infrared spectroscopy (NIRS) and diffuse optical imaging (DOI) are used in the scientific community to refer to the techniques used for noninvasive monitoring and imaging with diffuse light. Typically, light is injected into the medium and the signal re-emitted at some distance(s) on the surface is analyzed to retrieve information carried by photons along their paths. In the simplest case, continuous wave (CW) illumination and detection are employed.³ 4. ^{– 5} Conversely, the adoption either of a frequency-domain (FD)⁶ or of a time-domain (TD)⁷ 8. 9. ^{– 10} scheme permits to add a further dimension in the measurement, e.g., disentangling absorption from scattering contributions.

In recent years, diffuse optical spectroscopy (DOS) is advancing as a promising tool for noninvasive quantification of tissue constituents in pathological diagnostics.¹ 2. 3. ^{– 4} Traditionally, in vivo diffuse optical measurements have been performed, at most, in the 600- to 1100-nm window.⁵ 6. ^{– 7} This is due to high hemoglobin absorption below 600 nm and dominant water absorption combined with lack of suitable detection technology above 1100 nm. Furthermore, studies are most often performed below 900 nm, where more conventional and cheaper detectors are available. However, recent investigations emphasize the advantage of high penetration depth and enhanced constituent specificity in the short wave infrared (SWIR) 1100- to 1700-nm range.⁸ 9. ^{– 10} Importantly, the lack of systematic characterization of tissue constituents in the SWIR range prevents its widespread use for in vivo applications.

A multi-center study has been set up to accurately characterize the optical properties of diffusive liquid phantoms based on Intralipid and India ink at near-infrared (NIR) wavelengths. Nine research laboratories from six countries adopting different measurement techniques, instrumental set-ups, and data analysis methods determined at their best the optical properties and relative uncertainties of diffusive dilutions prepared with common samples of the two compounds. By exploiting a suitable statistical model, comprehensive reference values at three NIR wavelengths for the intrinsic absorption coefficient of India ink and the intrinsic reduced scattering coefficient of Intralipid-20% were determined with an uncertainty of about 2% or better, depending on the wavelength considered, and 1%, respectively. Even if in this study we focused on particular batches of India ink and Intralipid, the reference values determined here represent a solid and useful starting point for preparing diffusive liquid phantoms with accurately defined optical properties. Furthermore, due to the ready availability, low cost, long-term stability and batch-to-batch reproducibility of these compounds, they provide a unique fundamental tool for the calibration and performance assessment of diffuse optical spectroscopy instrumentation intended to be used in laboratory or clinical environment. Finally, the collaborative work presented here demonstrates that the accuracy level attained in this work for optical properties of diffusive phantoms is reliable.

Single-pixel camera imaging is an emerging paradigm that allows high-quality images to be provided by a device only equipped with a single point detector. A single-pixel camera is an experimental setup able to measure the inner product of the scene under view—the image—with any user-defined pattern. Postprocessing a sequence of point measurements obtained with different patterns permits to recover spatial information, as it has been demonstrated by state-of-the-art approaches belonging to the compressed sensing framework. In this paper, a new framework for the choice of the patterns is proposed together with a simple and efficient image recovery scheme. Our goal is to overcome the computationally demanding $\ell _1$ -minimization of the compressed sensing. We propose to choose patterns among a wavelet basis in an adaptive fashion, which essentially relies onto the prediction of the significant wavelet coefficients’ location. More precisely, we adopt a multiresolution strategy that exploits the set of measurements acquired at coarse scales to predict the set of measurements to be performed at a finer scale. Prediction is based on a fast cubic interpolation in the image domain. A general formalism is given so that any kind of wavelets can be used, which enables one to adjust the wavelet to the type of images related to the desired application. Both simulated and experimental results demonstrate the ability of our technique to reconstruct biomedical images with improved quality compared with compressive-sensing-based recovery. Application to the real-time fluorescence imaging of biological tissues could benefit from the proposed method.

In recent years, instruments and methodologies to noninvasively probe human tissues by diffuse light in the near-infrared spectral range have undergone translation from laboratory bench to bedside. For example, clinical trials have been performed targeting the female breast. Optical mammography has been developed and applied to detect and characterize breast lesions,^1,2 as well as to monitor the outcome of neoadjuvant chemotherapy of the breast.^3,4 Diffuse optical spectroscopy is a promising technique for cancer risk assessment.^5,6 In parallel, many clinical studies have been conducted targeting the brain. Optical imaging has been used to observe the hemodynamic response to cognitive, sensory, and motor stimuli,⁷ and to assess changes associated with traumatic brain injury,⁸ stroke,⁹ and epilepsy,¹⁰ with the aim of providing a less expensive and portable alternative to the existing neuroimaging techniques such as magnetic resonance imaging or x-ray computed tomography. Meanwhile, optical techniques have also been applied to other tissues such as muscle, joints, bone, and skin as a means of providing diagnostic information.

We propose a comprehensive statistical approach describing the penetration depth of light in random media. The presented theory exploits the concept of probability density function f(z|ρ, t) for the maximum depth reached by the photons that are eventually re-emitted from the surface of the medium at distance ρ and time t. Analytical formulas for f, for the mean maximum depth 〈z_max〉 and for the mean average depth "Equation missing" reached by the detected photons at the surface of a diffusive slab are derived within the framework of the diffusion approximation to the radiative transfer equation, both in the time domain and the continuous wave domain. Validation of the theory by means of comparisons with Monte Carlo simulations is also presented. The results are of interest for many research fields such as biomedical optics, advanced microscopy and disordered photonics.