Finite-element reconstruction method for space weighting of auto-fluorescence imaging

Abstract

The invention puts forward a finite-element reconstruction method for space weighting of auto-fluorescence imaging. The method uses a diffuse optical tomography (DOT) technique to precisely reconstruct optical parameters of main biological tissue. The method limits a possible real light-source region, and divides a whole reconstruction region into a light-source possible region and a light-source impossible region so as to improve the numerical stability and effectiveness of reconstruction problems and reduce the ill-conditioned property of BLT reconstruction problems. In order to avoid famous 'Inverse Crime' problems, the method adopts a Monte Carlo (MC) random method to simulate the process of transmitting light in the biological tissue. Then the invention puts forward a finite-element method based on a space-weighting unit and adopts a tolerant algorithm for linear constrained optimization problems to reconstruct light-source information.

Description

technical field [0001] The invention belongs to the field of molecular imaging, and relates to an autofluorescence tomography algorithm, in particular to a finite element reconstruction method applied to a space weighted unit of autofluorescence tomography. Background technique [0002] At this stage, autofluorescence tomography is gradually becoming an important technique for studying regions of interest at the cellular and molecular levels. BLT reconstructs the distribution and intensity information of fluorescent light sources in the near-infrared band from the photon measurements detected at the boundaries of the region of interest. In the region of interest, the biological self-luminescence light source is formed by fluorescent probes gathering in the region of interest (for example: tumor, region where physiological processes occur) and emitting fluorescence. This mechanism is currently commonly used in the tracking of immune cells and the real-time study of a large n...

AI Technical Summary

Problems solved by technology

At this stage, most of the BLT research groups in the world obtain the optical characteristic parameters of the main anatomical tissues through the literature, but in practice it is not accurate due to individual differences

On the other hand, the three-dimensional BLT light source inverse problem is very difficult to accurately reconstruct the light source intensity information because the number of internal unknown light sources is far greater than the amount of information that can be captured at the boundaries of biological tissues

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