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Comment on the modified Beer–Lambert law for scattering media

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Sassaroli, Angelo, Fantini, Sergio·2004·Physics in Medicine and Biology

DOI 10.1088/0031-9155/49/14/n07

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Abstract

We present a concise overview of the modified Beer-Lambert law, which has been extensively used in the literature of near-infrared spectroscopy (NIRS) of scattering media. In particular, we discuss one form of the modified Beer-Lambert law that is commonly found in the literature and that is not strictly correct. However, this incorrect form of the modified Beer-Lambert law still leads to the correct expression for the changes in the continuous wave optical signal associated with changes in the absorption coefficient of the investigated medium. Here we propose a notation for the modified Beer-Lambert law that keeps the typical form commonly found in the literature without introducing any incorrect assumptions.

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Delpy, D. T., Cope, M., van der Zee, P., Arridge, S., Wray, S., & Wyatt, J. S. (1988) · Physics in Medicine and Biology · doi:10.1088/0031-9155/33/12/008 · Cited by 2,251
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Kohl‐Bareis, M., Nolte, C. H., Heekeren, H. R., Horst, S., Scholz, U., Obrig, H., & Villringer, A. (1998) · Physics in Medicine and Biology · doi:10.1088/0031-9155/43/6/028 · Cited by 112
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Show all 7 references

Research works printed but not linked: 2

Boas D, Franceschini M A, Dunn A K and Strangman G 2002 Noninvasive imaging of cerebral activation with diffuse optical tomography In Vivo Optical Imaging of Brain Function ed D Ron Frostig (Boca Raton, FL: CRC Press) chapter 8, pp 193-211
Duderstadt J J 1979 Transport Theory (New York: Wiley)

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Authors: Sassaroli, A., & Fantini, S.
Affiliations: Tufts University (US)
ORCID: Sassaroli, Angelo
Fantini, Sergio
Venue: Physics in Medicine and Biology
Publisher: IOP Publishing
Published: 2004-07-06
Volume: 49
Issue: 14
Pages: N255-N257
ISSN: 0031-9155 (ISSN-L)
1361-6560
DOI: 10.1088/0031-9155/49/14/n07
OpenAlex: W2108329838
Cited by: 352
References: 7
Citations by year: 2026: 16 · 2025: 24 · 2024: 21 · 2023: 25 · 2022: 22 · 2021: 30 · 2020: 29 · 2019: 33 · 2018: 25 · 2017: 20 · 2016: 24 · 2015: 10 · 2014: 11 · 2013: 10 · 2012: 13
FWCI: 3.07
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: Physics in Medicine and Biology (publishedVersion)
PubMed (publishedVersion)
Funders: National Science Foundation
National Institutes of Health
National Institute on Drug Abuse (DA14178, R01DA014178)
Topics: Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Optical Imaging and Spectroscopy Techniques
Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Spectroscopy Techniques in Biomedical and Chemical Research
Physical Sciences › Chemistry › Analytical Chemistry › Spectroscopy and Chemometric Analyses
Keywords: modified Beer-Lambert law, turbid media, near-infrared spectroscopy, optical loss, absorption coefficient
MeSH terms: Biophysics, Image Processing, Computer-Assisted, Models, Theoretical, Scattering, Radiation, Statistics as Topic, Models, Statistical, Photons, Spectroscopy, Near-Infrared

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