Body fluid microscopic video lean expression method based on image fusion

Abstract

The invention discloses a body fluid microscopic video lean expression method based on image fusion, and the method comprises the steps: carrying out the extraction, fusion, sorting, non-maximum suppression and other technical processing of visible component key information in each frame of image based on an image fusion technology and an artificial intelligence visible component recognition technology; the effective information content in all videos in one view is expressed by pictures containing effective foreground and background information, so that the detection result is closer to the real state of a sample, the intelligent degree of the instrument is further improved, the checking speed of the detection result is greatly improved, and the detection efficiency is improved. The problems that when a full-automatic microscope is adopted for picture or video shooting analysis for body fluid visible component detection, due to the fact that a body fluid sample is thick and cannot be completely precipitated, focus fixing of the microscope is difficult, foreground and background information of different layers at the same position of the sample is difficult to completely reflect, and time and labor are wasted when videos need to be checked through manual auditing are solved; and the sample state cannot be directly and effectively expressed.

Description

technical field [0001] The invention relates to a lean expression method of body fluid microscopic video based on image fusion, in particular to a lean expression method of body fluid microscopic detection video. Background technique [0002] At present, in the microscopic examination of all body fluids formed components, most of them use an automatic microscope to take pictures or videos, and then perform image analysis. The image analysis method is due to the fact that when the body fluid sample is thick, the formed components in the sample cannot be completely precipitated, or the sample detection efficiency is low due to the long sedimentation time, or when the optical magnification is large, the image depth of field is small, and it is difficult to automatically control the focal length of the microscope. Fixed focus, and it is difficult to achieve complete detection of different tangible components at each level of the sample; although video shooting can be completely ...

AI Technical Summary

Problems solved by technology

Image analysis method Because when the body fluid sample is thick, the formed components in the sample cannot be completely precipitated, or the sample detection efficiency is low due to the long precipitation time, or when the optical magnification is large, the image depth of field is small, and the automatic control of the microscope focal length is difficult. Fixed focus, and it is difficult to achieve complete detection of different formed components at all levels of the sample; although video shooting can be fully detected, it is time-consuming and laborious to view the video during manual review, and cannot directly express the status of the formed components in the sample

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