2022
DOI: 10.1364/boe.449514
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Theoretical investigation of photon partial pathlengths in multilayered turbid media

Abstract: Functional near infrared spectroscopy (fNIRS) is a valuable tool for assessing oxy- and deoxyhemoglobin concentration changes (Δ[HbO] and Δ[HbR], respectively) in the human brain. To this end, photon pathlengths in tissue are needed to convert from light attenuation to Δ[HbO] and Δ[HbR]. Current techniques describe the human head as a homogeneous medium, in which case these pathlengths are easily computed. However, the head is more appropriately described as a layered medium; hence, the partial pathlengths in … Show more

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Cited by 7 publications
(15 citation statements)
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“…An advantage of the routine presented is that computing the fluence at 10 arbitrarily specified spatial locations takes only 3x longer than the times reported in Table 2. Although it can be difficult to directly compare computational times of different routines, as they depend highly on the computational resources and effort put into them, we were able to simulate the steady-state fluence 500-1,000x faster than previously reported 19,46 . We note that these times are achieved on a personal laptop using a single core.…”
Section: Discussionmentioning
confidence: 86%
See 1 more Smart Citation
“…An advantage of the routine presented is that computing the fluence at 10 arbitrarily specified spatial locations takes only 3x longer than the times reported in Table 2. Although it can be difficult to directly compare computational times of different routines, as they depend highly on the computational resources and effort put into them, we were able to simulate the steady-state fluence 500-1,000x faster than previously reported 19,46 . We note that these times are achieved on a personal laptop using a single core.…”
Section: Discussionmentioning
confidence: 86%
“…Several solutions for photon diffusion in layered media have been reported, but present technical difficulties for numerical computation. We have investigated a previously developed model 21,35 that has received wide interest 28,[44][45][46] . However, the model relies on numerical inverse transforms for obtaining the photon fluence for both steady-state and time-domain simulations which limits the numerical accuracy and speed.…”
Section: Discussionmentioning
confidence: 99%
“…An advantage of the routine presented is that computing the fluence at 10 arbitrarily specified spatial locations takes only 3× longer than the times reported in Table 2. Although it can be difficult to directly compare computational times of different routines, as they depend highly on the computational resources and effort put into them, we were able to simulate the steady-state fluence 500-1000× faster than previously reported 21,51 . We note that these times are achieved on a personal laptop using a single core.…”
Section: Discussionmentioning
confidence: 93%
“…Several solutions for photon diffusion in layered media have been reported, but present technical difficulties for numerical computation. We have investigated a previously developed model 23 , 37 that has received wide interest 30 , 47 , 48 , 51 . However, the model relies on numerical inverse transforms for obtaining the photon fluence for both steady-state and time-domain simulations which limits the numerical accuracy and speed.…”
Section: Discussionmentioning
confidence: 99%
“…Although different strategies have been implemented to overcome this issue 4 , the intrinsic model remains homogeneous, and the retrieved signal is susceptible of being corrupted by spurious influences from other tissues. Recently, some of the authors have developed a method to analytically compute the MPPLs in turbid media, consisting of up to four layers, in a matter of a few milliseconds 5 . In this way we have been able to demonstrate that the MPPLs strongly depend on the optical properties of each layer, as well as on its thicknesses and on the source-detector separation ρ, something which remains frequently neglected when using homogeneous models.…”
Section: Introductionmentioning
confidence: 99%