A cost function approach for the analysis of time-resolved functional near-infrared spectroscopy (TR fNIRS) signals

Junwoo Kim; Dug Young Kim

doi:10.1117/12.2289802

A cost function approach for the analysis of time-resolved functional near-infrared spectroscopy (TR fNIRS) signals

Junwoo Kim, Dug Young Kim

Department of Physics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Functional near-infrared spectroscopy (fNIRS) is a powerful clinical tool for monitoring hemoglobin concentration in brain tissues by analyzing absorption of scattered light. Since human brain is composed of multilayers including scalp, skull, and cerebral cortex, fNIRS signals need be analyzed with a multilayer tissue model. However, retrieving the optical properties of a multilayer tissue is often difficult because nonlinear fitting of absorption parameters from a scattered light signal by a tissue is ill-posed especially when the signal level is low. In this paper we introduce the cost function based masking technique for effective error minimization in the nonlinear fitting of fNIRS signals. We have shown that this method effectively reduces the influences of measurement errors with a newly defined cost function. Numerically simulated fNIRS data were generated for a two-layered tissue model and are used to extract the optical parameters of the two-layered tissue model. Accuracies of extracted parameters were compared with and without our proposed cost function.

Original language	English
Title of host publication	Dynamics and Fluctuations in Biomedical Photonics XV
Editors	Valery V. Tuchin, Ruikang K. Wang, Martin J. Leahy, Valery V. Tuchin, Kirill V. Larin
Publisher	SPIE
ISBN (Electronic)	9781510614710
DOIs	https://doi.org/10.1117/12.2289802
Publication status	Published - 2018
Event	Dynamics and Fluctuations in Biomedical Photonics XV 2018 - San Francisco, United States Duration: 2018 Jan 28 → 2018 Jan 29

Publication series

Name	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume	10493
ISSN (Print)	1605-7422

Other

Other	Dynamics and Fluctuations in Biomedical Photonics XV 2018
Country/Territory	United States
City	San Francisco
Period	18/1/28 → 18/1/29

Bibliographical note

Funding Information:
This work was financially supported by the National Research Foundation of Korea (NRF-2013R1A1A2062448) through the Basic Science Research Program, Global Frontier Project (CAMM-2014M3A6B3063712), the Ministry of Science and ICT of Korea, Technology Innovation Program (10062417), and the Ministry of Trade, Industry and Energy of Korea.

Publisher Copyright:
© 2018 SPIE.

All Science Journal Classification (ASJC) codes

Electronic, Optical and Magnetic Materials
Biomaterials
Atomic and Molecular Physics, and Optics
Radiology Nuclear Medicine and imaging

Access to Document

10.1117/12.2289802

Cite this

Kim, J., & Kim, D. Y. (2018). A cost function approach for the analysis of time-resolved functional near-infrared spectroscopy (TR fNIRS) signals. In V. V. Tuchin, R. K. Wang, M. J. Leahy, V. V. Tuchin, & K. V. Larin (Eds.), Dynamics and Fluctuations in Biomedical Photonics XV [104930U] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 10493). SPIE. https://doi.org/10.1117/12.2289802

Kim, Junwoo ; Kim, Dug Young. / A cost function approach for the analysis of time-resolved functional near-infrared spectroscopy (TR fNIRS) signals. Dynamics and Fluctuations in Biomedical Photonics XV. editor / Valery V. Tuchin ; Ruikang K. Wang ; Martin J. Leahy ; Valery V. Tuchin ; Kirill V. Larin. SPIE, 2018. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE).

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title = "A cost function approach for the analysis of time-resolved functional near-infrared spectroscopy (TR fNIRS) signals",

abstract = "Functional near-infrared spectroscopy (fNIRS) is a powerful clinical tool for monitoring hemoglobin concentration in brain tissues by analyzing absorption of scattered light. Since human brain is composed of multilayers including scalp, skull, and cerebral cortex, fNIRS signals need be analyzed with a multilayer tissue model. However, retrieving the optical properties of a multilayer tissue is often difficult because nonlinear fitting of absorption parameters from a scattered light signal by a tissue is ill-posed especially when the signal level is low. In this paper we introduce the cost function based masking technique for effective error minimization in the nonlinear fitting of fNIRS signals. We have shown that this method effectively reduces the influences of measurement errors with a newly defined cost function. Numerically simulated fNIRS data were generated for a two-layered tissue model and are used to extract the optical parameters of the two-layered tissue model. Accuracies of extracted parameters were compared with and without our proposed cost function.",

author = "Junwoo Kim and Kim, {Dug Young}",

note = "Funding Information: This work was financially supported by the National Research Foundation of Korea (NRF-2013R1A1A2062448) through the Basic Science Research Program, Global Frontier Project (CAMM-2014M3A6B3063712), the Ministry of Science and ICT of Korea, Technology Innovation Program (10062417), and the Ministry of Trade, Industry and Energy of Korea. Publisher Copyright: {\textcopyright} 2018 SPIE.; Dynamics and Fluctuations in Biomedical Photonics XV 2018 ; Conference date: 28-01-2018 Through 29-01-2018",

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Kim, J & Kim, DY 2018, A cost function approach for the analysis of time-resolved functional near-infrared spectroscopy (TR fNIRS) signals. in VV Tuchin, RK Wang, MJ Leahy, VV Tuchin & KV Larin (eds), Dynamics and Fluctuations in Biomedical Photonics XV., 104930U, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 10493, SPIE, Dynamics and Fluctuations in Biomedical Photonics XV 2018, San Francisco, United States, 18/1/28. https://doi.org/10.1117/12.2289802

A cost function approach for the analysis of time-resolved functional near-infrared spectroscopy (TR fNIRS) signals. / Kim, Junwoo; Kim, Dug Young.

Dynamics and Fluctuations in Biomedical Photonics XV. ed. / Valery V. Tuchin; Ruikang K. Wang; Martin J. Leahy; Valery V. Tuchin; Kirill V. Larin. SPIE, 2018. 104930U (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 10493).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N1 - Funding Information: This work was financially supported by the National Research Foundation of Korea (NRF-2013R1A1A2062448) through the Basic Science Research Program, Global Frontier Project (CAMM-2014M3A6B3063712), the Ministry of Science and ICT of Korea, Technology Innovation Program (10062417), and the Ministry of Trade, Industry and Energy of Korea. Publisher Copyright: © 2018 SPIE.

PY - 2018

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N2 - Functional near-infrared spectroscopy (fNIRS) is a powerful clinical tool for monitoring hemoglobin concentration in brain tissues by analyzing absorption of scattered light. Since human brain is composed of multilayers including scalp, skull, and cerebral cortex, fNIRS signals need be analyzed with a multilayer tissue model. However, retrieving the optical properties of a multilayer tissue is often difficult because nonlinear fitting of absorption parameters from a scattered light signal by a tissue is ill-posed especially when the signal level is low. In this paper we introduce the cost function based masking technique for effective error minimization in the nonlinear fitting of fNIRS signals. We have shown that this method effectively reduces the influences of measurement errors with a newly defined cost function. Numerically simulated fNIRS data were generated for a two-layered tissue model and are used to extract the optical parameters of the two-layered tissue model. Accuracies of extracted parameters were compared with and without our proposed cost function.

AB - Functional near-infrared spectroscopy (fNIRS) is a powerful clinical tool for monitoring hemoglobin concentration in brain tissues by analyzing absorption of scattered light. Since human brain is composed of multilayers including scalp, skull, and cerebral cortex, fNIRS signals need be analyzed with a multilayer tissue model. However, retrieving the optical properties of a multilayer tissue is often difficult because nonlinear fitting of absorption parameters from a scattered light signal by a tissue is ill-posed especially when the signal level is low. In this paper we introduce the cost function based masking technique for effective error minimization in the nonlinear fitting of fNIRS signals. We have shown that this method effectively reduces the influences of measurement errors with a newly defined cost function. Numerically simulated fNIRS data were generated for a two-layered tissue model and are used to extract the optical parameters of the two-layered tissue model. Accuracies of extracted parameters were compared with and without our proposed cost function.

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ER -

A cost function approach for the analysis of time-resolved functional near-infrared spectroscopy (TR fNIRS) signals

Abstract

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