cannot be done unless you involve a well-controlled physiological stimulus. The other drawback is that the measurement is often performed with only two wavelengths, the minimum necessary to retrieve two absorbing compounds [HbO\({}_{2}\)] and [HHb]. However, the contribution of other chromophores is either neglected (like collagen), or assumed and fixed, like water. This results in an increase in the physiological noise, which reduces the accuracy of the measurement. These drawbacks have been tackled over the recent years, and some new techniques and instrumentation enabled researchers to work around these drawbacks. Firstly, one can use more advanced CW-NIRS techniques in order to extract absolute information about the tissue. We can cite the broadband NIRS that also has the capability to extract absolute information of tissue optical properties [6]. The added benefits of this technique are that, as it uses a large number of wavelength (typically more than a hundred), it can perform a true spectroscopic analysis, hence also gathering information about other chromophores like cytochromes, water, and fat [6]. This extra information enables having a complete optical view of the tissue under investigations. Moreover, on top of providing a more precise view of the oxygenation, the use of many wavelengths enables targeting novel optical contrasts, like the oxidative state of the cytochrome-c-oxidase (oxCCO) which is a biomarker of metabolism [7]. However, even though these improvements are promising, performing a true spectroscopic measurement on tissue using NIRS is still challenging. One of the main issues is the penetration depth of the light and the contamination of the tissues of interest by the upper layers (i.e., skin) [3]. Indeed, the tissues are often modelled as homogeneous for simplicity, even though this hypothesis is not true. Therefore, new methodologies are required to enhance the discrimination between different tissue types, thus improving the accuracy of the measurement. It is well known that the time-domain NIRS (TD-NIRS) is the most advanced and accurate type of measurement, capable of retrieving absolute information and to discriminate between shallow and deep tissue [8]. Briefly, in TD-NIRS an ultra-short light impulse (typically in the picosecond range) illuminates the tissue. Tissue has the effect of attenuating and broadening the re-emitted pulse (the resulting pulse-width is typically few nanoseconds wide). The measured signal is typically called a temporal point spread function (TPSF) or distribution of time of flights (DTOFs) of photons. Indeed, what is measured here is the histogram of the arrival time of photons. Thus, the amount of information acquired by TD-NIRS systems outstrips the classical CW-NIRS, which only acquires the intensity. From these DTOF, various data processing methods can be employed to extract information about the tissue. It is out of the scope of this paper to detail these methods, but the interested reader can refer to the following reviews for a more in-depth description of TD-NIRS methodologies [9; 10], and for a special focus on broadband TD-NIRS [11], which will be largely discussed in the present work. The extraction of more accurate information with TD-NIRS comes at the cost of a more complex instrumentation, requiring pulsed-laser source (pulse in order of MHz) and fast electronic and sensitive detectors in order to be able to unlock single photon counting. Thus, even though TD-NIRS has been around for many decades now and has been developed in parallel to CW-NIRS, these more specific requirements have hindered its development. Nevertheless, much progress has been made over the last two decades, and TD-NIRS is closing the gap with CW-NIRS in terms of user's adoption. One of the key developments that has promoted the development of TD-NIRS is the supercontinuum laser (SCL) sources, which provide a white laser source, with a high power (several watts) and a very short pulse width (typical less than 10 ps) at several tens of MHz.