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Image recognition method and device, analysis instrument and storage medium

An image recognition and image technology, applied in the field of image processing, can solve the problems of large differences in grayscale pixels and shapes, and low recognition accuracy of image components.

Inactive Publication Date: 2019-02-15
MACCURA MEDICAL INSTR CO LTD
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Problems solved by technology

[0003] Due to the large differences in grayscale pixels and shapes of these formed components and impurity components, it is difficult to identify them one by one only through a single image processing technology, resulting in low accuracy of image component recognition

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  • Image recognition method and device, analysis instrument and storage medium
  • Image recognition method and device, analysis instrument and storage medium
  • Image recognition method and device, analysis instrument and storage medium

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Embodiment Construction

[0033] Features and exemplary embodiments of various aspects of the invention will be described in detail below. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the present invention.

[0034] Embodiments of the present invention provide an image recognition method and device, an analysis instrument, and a storage medium, which are used in medical equipment using image processing technology, such as a urine sediment analyzer. By adopting the technical solution in the embodiment of the present invention, the formed components and impurities in the image can be effectively identified based on the trained neural network, and the accuracy of image component identification can be improved.

[0035] Adaptive learning is an important function of neural networks. BP (back propagation) neural network is a multi-layer feed-forward neural network trained according to the error reverse propagation algorithm, a...

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Abstract

The invention discloses an image recognition method and device, an analysis instrument and a storage medium. The image recognition method comprises the following steps of extracting a plurality of eigenvalues of an effective connected region in a segmented image to be recognized, wherein the segmented image to be recognized includes an effective connected region; selecting m eigenvalues with the smallest correlation coefficient from a plurality of eigenvalues, wherein m is an integer greater than or equal to 2; according to the m eigenvalues and a preset neural network, obtaining the componentclasses of the effectively connected regions, training the preset neural network according to the multiple eigenvalues and the corresponding component classes extracted from the effectively connectedregions of a plurality of segmented images. The technical proposal in the embodiment of the invention can improve the accuracy of the image component identification.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an image recognition method and device, an analysis instrument and a storage medium. Background technique [0002] With the expansion of the application of image processing technology in the medical field, more and more medical devices need to realize their functions based on image processing technology. Taking the urine sediment analyzer as an example, its working principle is: the urine sample is photographed by a camera into an image sequence, and then image processing technology is used to realize the segmentation and identification of the formed components in each image. While improving the detection efficiency of the equipment, there are also Help reduce the workload of doctors. There are many formed elements in urine, including: red blood cells, white blood cells, crystals, sperm, hyaline casts, pathological casts, etc. In addition to the formed components, ther...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06T7/187
CPCG06T7/187G06T2207/30004G06F18/241G06F18/214
Inventor 徐宽张雅俊李奇武叶瑞夏刚
Owner MACCURA MEDICAL INSTR CO LTD
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