Tubercle bacillus target recognizing and counting algorithm based on diverse characteristics

A technology for Mycobacterium tuberculosis and target recognition, which is applied in the field of medical image processing and pattern recognition, and can solve problems such as inability to recognize and count

Inactive Publication Date: 2010-11-03
常州超媒体与感知技术研究所有限公司
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AI Technical Summary

Problems solved by technology

[0004] In order to overcome the existing deficiencies in the accurate, rapid and efficient identification and counting of Mycobacterium tuberculosis microscopic images after acid-fast staining, the present invention provides an algorithm for identifying and counting Mycobacterium tuberculosis targets based on multiple features

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  • Tubercle bacillus target recognizing and counting algorithm based on diverse characteristics
  • Tubercle bacillus target recognizing and counting algorithm based on diverse characteristics
  • Tubercle bacillus target recognizing and counting algorithm based on diverse characteristics

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Embodiment Construction

[0053] The present invention will now be described in further detail in conjunction with the accompanying drawings and preferred embodiments. These drawings are all simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, so they only show the configurations related to the present invention.

[0054] like Figure 9 A flow chart of the algorithm for identifying and counting mycobacterium tuberculosis targets based on multivariate features, a multivariate feature-based algorithm for identifying and counting mycobacterium tuberculosis targets, including the following steps:

[0055] 1. Image preprocessing, the specific operations are:

[0056] 1. Contrast enhancement, using the method of gray scale stretching to enhance the contrast of the original image.

[0057] 2. Median filtering, using a 3*3 template to perform median filtering on the contrast-enhanced image to filter out speckle noise.

[0058] 3. Gaussian f...

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Abstract

The invention relates to the field of medical image processing and mode recognition, in particular to a tubercle bacillus target recognizing and counting algorithm based on diverse characteristics. The algorithm comprises the following steps of: image preprocessing: carrying out image reinforcement and constructing median filter and Gaussian filter on a tubercle bacillus microimage; color image partition: carrying out fixed threshold partition based on HSV (Hue-Saturation-Value) color space on a preprocessed image and then carrying out adaptive threshold partition which is based on CIE L*a*b* color space and keeps a geometric shape of a target; communication block morphological analysis and target recognition: carrying out communication block analysis on the partitioned image; and tubercle bacillus target counting: estimating the quantity of tubercle bacillus targets in the image by utilizing a histogram statistics and multistrategy calculation method. The invention can effectively extract the bacillus targets in the tubercle bacillus microimage subjected to acid-fast stain from background and impurities and carry out accurate counting, thereby realizing the automation and the intellectualization of the detection of tubercle bacilli.

Description

technical field [0001] The invention relates to the fields of medical image processing and pattern recognition, in particular to a multiple feature-based recognition and counting algorithm for Mycobacterium tuberculosis targets. Background technique [0002] Pulmonary tuberculosis is one of the serious diseases that endanger human health. At present, the commonly used inspection methods include X-ray chest fluoroscopy, tuberculosis culture and direct microscope smear test for sputum. X-ray chest fluoroscopy is not easy to distinguish from other lung diseases; tuberculosis culture method is accurate and reliable, but it takes a long time, usually 4 to 8 weeks, which affects the patient's treatment time; direct smear smear test method with microscope is fast and simple, but this method It relies heavily on the knowledge and experience of pathologists, has very high requirements for experts, and cannot give quantitative results, which may easily lead to missed diagnosis. [00...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06M11/00G06T5/00G06K9/00
Inventor 刘云辉翟永平刘顺周东翔蔡宣平
Owner 常州超媒体与感知技术研究所有限公司
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