Fluorescence molecular tomography reconstruction method based on sparsity self-adaptive group orthogonal matching pursuit

Abstract

The invention belongs to the field of optical molecular imaging, and particularly relates to a fluorescence molecular tomography reconstruction method based on sparsity self-adaptive group orthogonalmatching pursuit, in order to solve problems of excessive-sparse zones, spatial discontinuity and poor process robust performance in tumor distribution solving utilizing sparse constraint optimizationin the prior art. The method includes subjecting biological CT three-dimensional data to partitioning and finite element discretization, and performing fusion of the data with biology body surface excited fluorescence image data; building a model according to light intensity distribution information of the body surface excited fluorescence after fusion; dividing the model and constructing a localspatial continuity constraint condition; integrating L1 norm sparsity and performing iterative solution to obtain aggregation distribution of probes in a biological tumor zone. Through fusion of thespatial structure constraint and the sparse constraint, a novel spatial structure sparse regularization term is constructed, and problems of excessive-sparse zones, spatial discontinuity and poor process robust performance, which are caused by a manner that tumor distribution is solved only based on a sparse constraint, can be solved.

Description

technical field [0001] The invention belongs to the technical field of optical molecular imaging, and in particular relates to an excitation fluorescence tomographic reconstruction method, system and device for sparseness self-adaptive group orthogonal matching tracking. Background technique [0002] Fluorescence Molecular Tomography (FMT, Fluorescence Molecular Tomography), as a new type of optical molecular imaging technology, uses specific probes to target and mark tumor cells, and under the irradiation of an external excitation light source of a specific wavelength, the fluorescent probes absorb energy to generate The electron energy level jumps, generates excitation light and penetrates the biological tissue in the body to reach the body surface and is captured by a high-sensitivity optical detector in vitro. The diffusion equation model of photon transmission in biological tissue is established through the tissue structure information provided by computerized tomograph...

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Problems solved by technology

[0005] In order to solve the above problems in the prior art, that is, the prior art uses sparsity-constrained optimization to solve the problems of over-sparse region, discontinuous space, and less robust process in the tumor dist

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