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Human feces leukocyte automatic recognition method based on machine learning

A machine learning and automatic recognition technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve problems such as large amount of calculation, and achieve the effect of small amount of calculation, high speed and high efficiency

Active Publication Date: 2018-09-21
UNIV OF ELECTRONICS SCI & TECH OF CHINA +1
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  • Description
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Problems solved by technology

[0003] The applicant has applied for a patent for an automatic detection method for white blood cells in bronchoalveolar lavage smears in 14 years (patent number is 2014103696359). Degree and binarization processing, while using the appearance and internal features of white blood cells to screen, and finally identify white blood cells, using pure image processing methods to detect white blood cells in the sample, the amount of calculation is large in practical applications

Method used

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  • Human feces leukocyte automatic recognition method based on machine learning
  • Human feces leukocyte automatic recognition method based on machine learning
  • Human feces leukocyte automatic recognition method based on machine learning

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Embodiment Construction

[0050] A detection method for human feces leukocytes, the method comprising the following steps:

[0051] Step 1: Perform pretreatment operations such as dilution, stirring, and sedimentation on human feces, and use a biological microscope to collect microscopic images of human feces samples.

[0052] Step 2: Perform grayscale processing on the image in step 1 and convert it into a grayscale image.

[0053] Step 3: Perform local inverse binarization processing on the grayscale image in step 2 to obtain a binarized image. The local processing area is a square with a radius of 11; the threshold selection method is gray mean value, and the threshold scaling factor is 0.98.

[0054] Step 4: Carry out a hole filling operation on the binary image in step 3, and then remove the area with an area smaller than 200.

[0055] Step 5: Perform morphological expansion on the binary image in step 4, using a circular template with a radius of 4. Hole filling is performed on the dilated bin...

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Abstract

The invention discloses a human feces leukocyte automatic recognition method based on machine learning and relates to processing technologies based on digital images, in particular to an automatic recognition and detection method for leukocytes in human feces based on the machine learning technology. According to the method, feature extraction is performed on a sample image, extracted features areadopted to train an SVM (support vector machine), and then the trained vector machine is applied to leukocyte recognition. The method has the advantages of being accurate in recognition, high in speed, high in efficiency and small in calculation amount.

Description

technical field [0001] The invention relates to a method for automatically identifying and detecting white blood cells in human feces based on digital image processing technology, especially machine learning technology. Background technique [0002] Leukocytes in human feces are often detected in mucus and pus and blood, and most of them are neutrophil granulocytes. Due to cell degeneration, the cells are swollen and the structure is unclear. If the number is large, there are piles, and the cell membrane is incomplete or broken, it is also called pus cells at this time, indicating that the infection is serious. Unlike human blood and urine, human feces contain a large amount of impurities such as food residues, resulting in complex image backgrounds; some white blood cell membranes are no longer complete and adhere to some impurities. All of the above reasons lead to the difficulty of dividing white blood cells. Due to the degeneration of cells, the morphology of leukocyt...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/214G06F18/2411
Inventor 刘娟秀王祥舟申志杰邓鼎文杜晓辉赵家喜张静倪光明郝如茜刘霖刘永周辉
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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