By adopting a microscopy-based setup and DOT imaging principles, LOT/MFMT can perform 3-D imaging with higher resolution 100 to than DOT and deeper penetration (2 to 3 mm) than confocal and two-photon microscopy while there is always a trade-off between axial resolution and penetration depth. Due to the limited penetration depth of LOT/MFMT, thinning or exposing the skull is usually necessary when imaging the cortical hemodynamic responses or neural activities using LOT/MFMT, which indicates that imaging the brain with LOT/MFMT is mainly applicable in small-sized animals.3,27 In such cases, LOT/MFMT has been focused to applications in which tissues of interest are superficial, such as the exposed mouse brain and skin, as well as oncological applications.24,74,34,99 For instance, LOT/MFMT has been applied to image skin cancers to describe the depth and thickness of pigmented skin lesions in clinical settings99 and has also been employed to image the biodistribution of a photodynamic therapeutic agent with ultrasound co-registration in skin cancer models in vivo, though we can see there is still a long way to human clinical translation.74 Imaging of internal organs using LOT/MFMT can be potentially achieved via endoscopic, intraluminal, or an intrasurgical imaging setup.24 Laser scanning microscopy (e.g., confocal and two-photon microscopy) aims to reject light that has been scattered to obtain high-resolution images of the tissue either by isolating the signal from the focus using a conjugated pinhole or by employing the nonlinear effect.100,101 Instead, LOT/MFMT takes advantage of the scattered light so that they are much more sensitive to the optical signal changes in the tissue. LOT/MFMT obtains depth-resolved information by measuring the scattered light emerging from the tissue using detectors at different distances from the source illumination position, instead of scanning the tissue in the axial direction, which can dramatically improve the data acquisition efficiency. On the other hand, since the detected light undergoes multiple scattering in the tissue, the resolution of LOT/MFMT cannot compete with laser scanning microscopy. Moreover, estimation of photon migration using the mathematical models could not be exact, especially for the complicated biological tissues and the path of photons that become more uncertain as they scatter further. LOT/MFMT faces resolution deterioration of these reconstructed images as a function of depth.3,24,28 A combination of dense spatial datasets with regularization terms like compressive sensing-based methods has the potential to push LOT/MFMT resolution close to or beyond, even at depths of several millimeters.40 In terms of image visualization, since laser scanning microscopy uses a more “direct” way to obtain intensity of every pixel in the image, it can achieve nearly real-time image feedback. While applying MC modeling and regularization term to solve the inverse problem, LOT/MFMT has a high computational burden and is time-consuming especially for a system with high source–detector density, as mentioned in Sec. 2.4. As a result, for now, LOT/MFMT cannot provide the reconstructed image in real time, perhaps restricting the translation to clinical applications. With the advent of the supercomputer, the time needed for high-burden computation in LOT/MFMT could be alleviated significantly.