Rat brain section microscopic image segmentation method based on markov random field theory

A Markov random field and microscopic image technology, applied in image analysis, image data processing, instruments, etc., can solve the problem that Gaussian distribution cannot accurately describe noise and cell grayscale information.
CN103208124AInactive Publication Date: 2013-07-17NORTHWESTERN POLYTECHNICAL UNIV
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
NORTHWESTERN POLYTECHNICAL UNIV
Publication Date
2013-07-17
Estimated Expiration
Not applicable Β· inactive patent

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Abstract

The invention relates to a rat brain section microscopic image segmentation method based on a markov random field theory. Gaussian mixed distribution is trained through the existing tagged image and used in characteristic field modeling, image characteristics are simulated correctly, great guiding significance for random field modeling is obtained, convergence times of an iterative algorithm are greatly reduced, and the accuracy of a segmentation result is improved. In addition, in order to solve the problem that local neighborhood characteristics of a traditional 8 neighborhood pixel model traced image are too rough, the method introduces a pixel gray value and a distance between pixels into a Potts model, a new potential-energy function is defined, image local information is described correctly, and the accuracy of a segmentation result is improved.
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Description

technical field

[0001] The invention belongs to the technical field of biological microscopic image processing, and in particular relates to a method for segmenting microscopic images of mouse brain slices based on Markov random field theory. Background technique

[0002] Segmentation of cells in microscopic images is a fundamental problem in the research fields of biology and life sciences. Microscopic images of mouse brain slices are images of brain tissue observed under a high-resolution microscope, in which accurate identification of nerve cells is of great significance for in-depth analysis of biological genetic and metabolic mechanisms. In the early stage of the experiment, the green fluorescent protein gene was added to the FOS gene of the mouse. When the FOS gene was expressed into C-FOS protein in the nerve cells, the fluorescent protein gene bound to it was expressed at the same time. Through molecular microscope photography, the fluorescent protein gene containing...

Claims

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