A fixed-point noise location and evaluation method for sperm microenvironment cleanliness

Abstract

The invention discloses a method for locating fixed-point noise and evaluating the cleanliness of sperm microscopic environment. The first step is to model the sperm video to obtain a background image containing fixed-point noise; the second step is to use neutronic grayscale and neutrophilic gray scale. The fusion information of the two gradient features separates the fixed-point noise from the background pixels; Step 3: Adjust the noise factor to adjust the similarity between the pixels and the ideal background pixels, control the particle size of the extracted fixed-point noise, and combine the sperm fixed-point noise and Impurities and solid point noise are separated. The fixed-point noise extraction algorithm based on the noise adjustment factor can extract the sperm fixed-point noise and the impurity fixed-point noise separately, and can calculate the imprecision ratio index. Able to measure the cleanliness of the microscopic environment.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a method for locating fixed-point noise and evaluating the cleanliness of a sperm microenvironment. Background technique [0002] Semen testing is an important basis for evaluating male fertility. Computer-aided sperm quality analysis system has become the development trend of sperm quality analysis because of its objectivity and accuracy. [0003] In the 20X sperm microscope observation field, under the magnification of the microscope, static sperm, impurities, dust, air bubbles, lens pollutants, etc., form a particle image with a fixed position and a darker gray scale. We collectively refer to these particles with a fixed position as Fixed point noise. Among them, the particle noise formed by static sperm is called sperm fixed point noise; the particle noise formed by impurities, dust, air bubbles and dirt is called impurity fixed point noise. The amount of impurity ...

AI Technical Summary

Problems solved by technology

[0005] (1) The fixed-point noise of sperm and the fixed-point noise of impurities cannot be effectively separated, and the extracted sperm fixed-point noise is mixed with part of the fixed-point noise of impurities;

[0006] (2) For video images without obvious bimodal distribution, especially for images with static sperm sparseness, traditional segmentation algorithms such as the maximum inter-class difference cannot separate the fixed-point noise of sperm from the image at all;

[0007] (3) Since the gray scale of the dynamic sperm trajectory is similar to the fixed point noise of some impurities, it is difficult to effectively separate the two

[0008] At present, due to the lack of an effective solid-point noise extraction algorithm, the dynamic sperm trajectory, sperm fixed-point noise, and impurity solid-point noise cannot be effectively separated. The analysis system lacks quality control indicators for the cleanliness of the microenvironment

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