Quick Monte Carlo imaging method for reconstructing optical parameter of tissue with heteroplasmon

Abstract

The invention belongs to the technical field of biomedical engineering, and relates to a quick Monte Carlo imaging algorithm for reconstructing an optical parameter of a tissue with a heteroplasmon. The algorithm comprises the steps of confirming a detection zone, axially subdividing the detection zone, selecting intersection points of subdivision grid lines as scanning points, obtaining diffuse reflection light distribution in different scanning positions, performing MC (Monte Carlo) simulation when an illuminant is located at an original point and detectors are symmetrically distributed on the two sides of the illuminant, and obtaining mean collision times and mean walking lengths of photons in volume elements and photon weights received by all the detectors, Step III, restoring the collision times and the walking lengths in the volume elements when source detectors are positioned in all the scanning points, calculating and outputting weights of the photons, and determining a Jacobi matrix, Step IV, working out a position and the optical parameter of the heteroplasmon. The method has the benefits that the optical parameter of the tissue with the heteroplasmon can be reconstructed; the pMC (perturbation Monte Carlo) algorithm is optimized; a memory space is saved; and the calculation time is shortened.

Description

technical field [0001] The invention belongs to the technical field of biomedical engineering and relates to a diffuse light functional tomography algorithm suitable for mesoscopic and medium spatial resolution. Background technique [0002] Cancer can not only lead to changes in tissue structure and cell morphology, but also changes in functional metabolic activities. The development of functional imaging technology can provide a more objective and specific basis for the diagnosis of early cervical cancer. At present, for thin-layer epithelial tissues such as cervix and skin, diffuse light functional tomography with mesoscopic and medium spatial resolution is mainly used. However, when the detection distance is less than 1mm, both the diffusion equation and the more complex hybrid-diffusion-P3 approximation equation have large errors in describing the propagation of light in tissue. Given the Monte Carlo simulation (MC) [1] In describing the wide applicability of light pr...

AI Technical Summary

Problems solved by technology

However, due to the need to run a complete MC simulation to obtain the path of the photon in the tissue to obtain k and s, the current pMC algorithm is limited to the reconstruction of the optical parameters of the homogeneous medium, or the position of the heterogeneous body is known. Reconstruction of the optical parameters of the heterogeneous body in the case of , which is far from the actual demand

In addition, in order to save the walking path of photons, it not only takes up a lot of storage space, but also seriously increases the calculation time of the reconstruction process

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