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We recently developed a time-domain technique for localizing in 3D discrete fluorescent inclusions embedded
in a scattering medium. It exploits early photon arrival times (EPATs), that is the time of flight of early
arriving photons at a detector determined via numerical constant fraction discrimination. Our localization
technique requires the knowledge of the speed of propagation of diffuse light pulses in the turbid medium to
convert measured propagation times to distances. We have developed an experimental method for measuring
the speed of propagation of such pulses. We have shown that time differences between a reference detector
position and other positions around the medium allow finding the position of the inclusion. Our technique allows
localizing inclusions to millimeter precision in a thick 5 cm diameter turbid medium. Herein, we analyze the
stability of EPAT differences introduced above and propagation speeds with respect to changes in the medium's
optical properties for optical properties typical of biological tissues. As we target small animal imaging, we
concentrate on optical properties of mouse organs and tissues. Our objective is to determine bounds to be
expected on the precision that can be achieved when media properties can vary and determine the limits of
validity of our localization technique. Our results show that EPAT differences and propagation speeds obtained
by our approach can vary; these values depend on the medium. We study 5 kinds of mouse organs and tissues.
Propagations speeds are between 2.97 × 107ms-1 and 5.52 × 107ms-1. Thus, it becomes important to evaluate
the discrepancy between true geometrical distance differences and distances as obtained by our approach using a
constant propagation speed and the measurement of EPAT differences. It is such discrepancies that ultimately
determine the localization accuracy of our algorithm because if distance differences based on EPATs are far from
true distances, our algorithm although it has a certain tolerance will have to consider that. The distance error
and so the localization accuracy of our algorithm is between 2.5mm and 8.6mm.
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