Abstract
We conducted a systematic investigation of the reflectance diffuse optical tomography using continuous wave (CW) measurements and nonlinear reconstruction algorithms. We illustrated and suggested how to fine-tune the nonlinear reconstruction methods in order to optimize target localization with depth-adaptive regularizations, reduce boundary noises in the reconstructed images using a logarithm based objective function, improve reconstruction quantification using transport models, and resolve crosstalk problems between absorption and scattering contrasts with the CW reflectance measurements. The upgraded nonlinear reconstruction algorithms were evaluated with a series of numerical and experimental tests, which show the potentials of the proposed approaches for imaging both absorption and scattering contrasts in the deep targets with enhanced image quality.
Highlights
Due to the numerous advantages of low cost, portability, and non-ionizing radiation, nearinfrared (NIR) diffuse optical tomography (DOT) is emerging as a potential tool for imaging biological tissues
With optimization algorithms and regularization techniques utilized in the inverse problem, the distribution of optical/physiological properties of tissues can be recovered quantitatively by minimizing the difference between the model predicted data and the measured data [6]
We implemented a systematic investigation of reflectance DOT based on the nonlinear reconstruction method and continuous wave (CW) measurements
Summary
Due to the numerous advantages of low cost, portability, and non-ionizing radiation, nearinfrared (NIR) diffuse optical tomography (DOT) is emerging as a potential tool for imaging biological tissues. With optimization algorithms and regularization techniques utilized in the inverse problem, the distribution of optical/physiological properties of tissues can be recovered quantitatively by minimizing the difference between the model predicted data and the measured data [6]. While both linear and non-linear reconstruction algorithms are available, considerable efforts have been made to develop various nonlinear algorithms [7]. The DA is not accurate enough to model light transport in some tissue regions including low scattering fluid-filled and high-absorption vascular tissues in human brains To overcome this limitation, we have developed a 3D reconstruction method based on simplified spherical harmonics approximated-RTE [11]. To overcome the absorption-scattering crosstalk issue, we applied the absorption coefficient priors in the reflectance DOT reconstruction algorithms and its efficacy was validated
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