Suppressing physiological interferences and physical noises in functional diffuse optical tomography via tandem inversion filtering and LSTM classification.

Abstract

For performance enhancement of functional diffuse optical tomography (fDOT), we propose a tandem method that takes advantage of the inversion filtering and the long short term memory (LSTM) classification to simultaneously suppress the physiological interferences and physical noises in fDOT. In the former phase, the absorption perturbation maps over the scalp-skull (SS) and cerebral-cortex (CC) layers are firstly pre-reconstructed using a two-layer topography scheme. Then, the recovered SS-map is inversed into measurement space by the forward calculation to estimate the intensity changes associated with the physiological interferences. Finally, the raw measurements are adaptively filtered with reference to the estimated intensity changes for accomplishing the model-based full three-dimension (3D) reconstruction. In the later phase, for further removing the randomly distributed physical noises, mainly instrumental noise, a LSTM network based fusion strategy is applied, where a pixel-wise binary mask of "activated" or "inactive" state is generated by performing LSTM classification and then fused with the 3D reconstruction. The results of the simulative investigation and in-vivo experiment show the proposed tandem scheme achieves improved performance in fDOT using a cost-effective and physically explicable way. Thus, the proposed method can be promisingly applied in real-time neuroimaging to acquire cortical neural activation information with improved reliability, quantification and resolution.