Cerebral blood flow monitoring using a ConvGRU model based on diffuse correlation spectroscopy - Details

Author：

Feng, J. (Feng, J..) | Jiang, M. (Jiang, M..) | Bai, J. (Bai, J..) | Jia, K. (Jia, K..) | Li, Z. (Li, Z..)

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Abstract：

Continuous　monitoring　of　cerebral　blood　flow　(CBF)　provides　crucial　information　for　clinical　diagnosis　and　treatment　of　various　cerebral　diseases.　Diffuse　correlation　spectroscopy　(DCS)　uses　near-infrared　(NIR)　coherent　point-source　illumination　to　accommodate　spectroscopic　measurements　of　CBF　variations.　In　this　paper,　we　investigate　and　evaluate　a　deep　learning　method　for　CBF　quantification　based　on　proposed　ConvGRU　model.　Two　in　vivo　experiments,　i.e.,　deep-breath　experiment　and　breath-holding　experiment,　were　established　to　measure　normalized　intensity　autocorrelation　function　data.　Compared　to　conventional　methods,　promising　results　for　assessing　changes　of　CBF　were　gained　by　the　developed　ConvGRU　models.　Our　results　suggest　that　ConvGRU-based　deep　learning　method　can　provide　an　alternative　method　for　continuous　monitoring　of　CBF.　©　2023　Elsevier　B.V.

Keyword：

Cerebral blood flow (CBF) Breath-holding Diffuse correlation spectroscopy (DCS) Deep breath ConvGRU model

Author Community：

[ 1 ] [Feng J.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
[ 2 ] [Feng J.]Beijing Laboratory of Advanced Information Networks, Beijing, 100124, China
[ 3 ] [Jiang M.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
[ 4 ] [Jiang M.]Beijing Laboratory of Advanced Information Networks, Beijing, 100124, China
[ 5 ] [Bai J.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
[ 6 ] [Bai J.]Beijing Laboratory of Advanced Information Networks, Beijing, 100124, China
[ 7 ] [Jia K.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
[ 8 ] [Jia K.]Beijing Laboratory of Advanced Information Networks, Beijing, 100124, China
[ 9 ] [Li Z.]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
[ 10 ] [Li Z.]Beijing Laboratory of Advanced Information Networks, Beijing, 100124, China

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Related Keywords：

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Source ：

Infrared Physics and Technology

ISSN： 1350-4495

Year： 2023

Volume： 129

3 . 3 0 0

JCR@2022

ESI Discipline： PHYSICS;

ESI HC Threshold：17

Cited Count：

WoS CC Cited Count： 0

SCOPUS Cited Count： 11

ESI Highly Cited Papers on the List： 0 Unfold All

WanFang Cited Count：

Chinese Cited Count：

30 Days PV： 5

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