8 February 2018 Towards real-time diffuse optical tomography for imaging brain functions cooperated with Kalman estimator
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Abstract
Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging method to monitor the cerebral hemodynamic through the optical changes measured at the scalp surface. It has played a more and more important role in psychology and medical imaging communities. Real-time imaging of brain function using NIRS makes it possible to explore some sophisticated human brain functions unexplored before. Kalman estimator has been frequently used in combination with modified Beer-Lamber Law (MBLL) based optical topology (OT), for real-time brain function imaging. However, the spatial resolution of the OT is low, hampering the application of OT in exploring some complicated brain functions. In this paper, we develop a real-time imaging method combining diffuse optical tomography (DOT) and Kalman estimator, much improving the spatial resolution. Instead of only presenting one spatially distributed image indicating the changes of the absorption coefficients at each time point during the recording process, one real-time updated image using the Kalman estimator is provided. Its each voxel represents the amplitude of the hemodynamic response function (HRF) associated with this voxel. We evaluate this method using some simulation experiments, demonstrating that this method can obtain more reliable spatial resolution images. Furthermore, a statistical analysis is also conducted to help to decide whether a voxel in the field of view is activated or not.
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Bingyuan Wang, Bingyuan Wang, Yao Zhang, Yao Zhang, Dongyuan Liu, Dongyuan Liu, Xuemei Ding, Xuemei Ding, Mai Dan, Mai Dan, Tiantian Pan, Tiantian Pan, Yihan Wang, Yihan Wang, Jiao Li, Jiao Li, Zhongxing Zhou, Zhongxing Zhou, Limin Zhang, Limin Zhang, Huijuan Zhao, Huijuan Zhao, Feng Gao, Feng Gao, } "Towards real-time diffuse optical tomography for imaging brain functions cooperated with Kalman estimator", Proc. SPIE 10480, Clinical and Translational Neurophotonics 2018, 104800T (8 February 2018); doi: 10.1117/12.2291732; https://doi.org/10.1117/12.2291732
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