Laminar optical tomography (LOT) is a new mesoscopic functional optical imaging technique. Currently, the forward problem of LOT image reconstruction is generally solved on the basis of Monte-Carlo (MC) methods. However, considering the nonlinear nature of the image reconstruction in LOT, with the increasing number of source positions, methods based on MC takes too much computation time. Based on the scheme of trajectory translation and target voxel regression (TT&TVR) proposed by our group, this paper develops a fast 3D image reconstruction algorithm. The algorithm is applied to the absorption reconstruction of the layered inhomogeneous media. Results demonstrate that the reconstructing time is less than 15min with the X-Y-Z section of the sample subdivided into 50 × 50 × 10 voxels, and the target size and quantitativeness ratio can be obtained in a satisfying accuracy.
Laminar optical tomography (LOT) is a new mesoscopic functional optical imaging technique, which is an extension of a confocal microscope and diffuse optical tomography to acquire both the coaxial and off-axis scattered light at the same time. In this paper, a LOT system with a larger detection area aiming at the in vivo detection of early cervical cancer is developed. The field of view of our system is 10 mm x 10 mm. In order to improve the image quality of the system, two methods were performed: the correction of image distortion and the restriction of returning light. The performance of the system with aperture stop was assessed by liquid phantom experiments. Comparing with the Monte Carlo simulation, the measurement results show that the average relative errors of eight different source-detector distances corresponding to 4 source points are lower than the errors of the system taking the frame of objective lens as the aperture stop by 5.7%, 4.8%,6.1%,6.1% respectively. Moreover, the experiment based on the phantom with specified structure and optical parameters to simulate the cervix demonstrates that the system perform well for the cervix measurement.
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