Chinese Journal of Lasers, Volume. 50, Issue 21, 2107107(2023)
Deep Convolutional Encoder‑Decoder Neural Network Approach for Functional Near Infrared Spectroscopic Imaging
[1] Althobaiti M, Al-Naib I. Recent developments in instrumentation of functional near-infrared spectroscopy systems[J]. Applied Sciences, 10, 6522(2020).
[2] Herold F, Wiegel P, Scholkmann F et al. Applications of functional near-infrared spectroscopy (fNIRS) neuroimaging in exercise-cognition science: a systematic, methodology-focused review[J]. Journal of Clinical Medicine, 7, 466(2018).
[3] Fishell A K, Burns-Yocum T M, Bergonzi K M et al. Mapping brain function during naturalistic viewing using high-density diffuse optical tomography[J]. Scientific Reports, 9, 11115(2019).
[4] Aihara T, Shimokawa T, Ogawa T et al. Resting-state functional connectivity estimated with hierarchical Bayesian diffuse optical tomography[J]. Frontiers in Neuroscience, 14, 32(2020).
[5] Duan L, Zhao Z P, Lin Y L et al. Wavelet-based method for removing global physiological noise in functional near-infrared spectroscopy[J]. Biomedical Optics Express, 9, 3805-3820(2018).
[6] Intes X, Ntziachristos V, Culver J P et al. Projection access order in algebraic reconstruction technique for diffuse optical tomography[J]. Physics in Medicine and Biology, 47, N1-N10(2002).
[7] Cao X, Zhang B, Wang X et al. An adaptive Tikhonov regularization method for fluorescence molecular tomography[J]. Medical & Biological Engineering & Computing, 51, 849-858(2013).
[8] Li A, Miller E L, Kilmer M E et al. Tomographic optical breast imaging guided by three-dimensional mammography[J]. Applied Optics, 42, 5181-5190(2003).
[9] Brooksby B A, Dehghani H, Pogue B W et al. Near-infrared (NIR) tomography breast image reconstruction with a priori structural information from MRI: algorithm development for reconstructing heterogeneities[J]. IEEE Journal of Selected Topics in Quantum Electronics, 9, 199-209(2003).
[10] Wang H Q, Wu N, Zhao Z et al. Diffuse optical tomography reconstruction based on deep learning[J]. Laser & Optoelectronics Progress, 57, 040003(2020).
[11] Cai C J, Deng K X, Ma C et al. End-to-end deep neural network for optical inversion in quantitative photoacoustic imaging[J]. Optics Letters, 43, 2752-2755(2018).
[12] Feng J C, Sun Q W, Li Z et al. Back-propagation neural network-based reconstruction algorithm for diffuse optical tomography[J]. Journal of Biomedical Optics, 24, 051407(2018).
[13] Liu D Y, Zhang P R, Zhang Y et al. Suppressing physiological interferences and physical noises in functional diffuse optical tomography via tandem inversion filtering and LSTM classification[J]. Optics Express, 29, 29275-29291(2021).
[14] Bonomini V, Zucchelli L, Re R et al. Linear regression models and k-means clustering for statistical analysis of fNIRS data[J]. Biomedical Optics Express, 6, 615-630(2015).
[15] Yamada Y, Okawa S. Diffuse optical tomography: present status and its future[J]. Optical Review, 21, 185-205(2014).
[16] Liu D Y, Zhang Y, Bai L et al. Combining two-layer semi-three-dimensional reconstruction and multi-wavelength image fusion for functional diffuse optical tomography[J]. IEEE Transactions on Computational Imaging, 7, 1055-1068(2021).
[17] Ding X M, Wang B Y, Liu D Y et al. Multi-channel brain functional imaging system based on lock-in photon counting[J]. Chinese Journal of Lasers, 46, 0107001(2019).
Get Citation
Copy Citation Text
Tieni Li, Dongyuan Liu, Pengrui Zhang, Zhiyong Li, Feng Gao. Deep Convolutional Encoder‑Decoder Neural Network Approach for Functional Near Infrared Spectroscopic Imaging[J]. Chinese Journal of Lasers, 2023, 50(21): 2107107
Category: Biomedical Optical Imaging
Received: Apr. 17, 2023
Accepted: May. 29, 2023
Published Online: Nov. 7, 2023
The Author Email: Feng Gao (gaofeng@tju.edu.cn)