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Intelligent analysis system and method for labial gland pathology

An intelligent analysis and labial gland technology, applied in the medical field, can solve problems such as non-standard, difficult, and inaccurate clinical operations, and achieve the effects of making up for large measurement errors, facilitating clinical application, and shortening the time for interpretation of results

Pending Publication Date: 2021-11-30
SUN YAT SEN MEMORIAL HOSPITAL SUN YAT SEN UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is to overcome the non-standard, inaccurate and difficult clinical operation problems in the pathological diagnosis technology of Sjogren's syndrome lip glands in the above-mentioned prior art, and provide a kind of intelligent analysis system and method for evaluating the pathology of lip glands, aiming at Let pathologists, rheumatologists and immunologists, and even patients themselves scan the stained lip gland tissue HE slices into digital pathological images, and upload them to this intelligent analysis method and system to learn the precise lip gland focal index and Compare and judge whether it meets the "gold standard" of labial gland pathology in Sjogren's syndrome, that is, the focal index of labial glands is ≥1

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  • Intelligent analysis system and method for labial gland pathology
  • Intelligent analysis system and method for labial gland pathology
  • Intelligent analysis system and method for labial gland pathology

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Embodiment 1

[0059] Example 1: Intelligent analysis method for labial gland pathology

[0060] A method for intelligent analysis of labial gland pathology, comprising the steps of:

[0061] S1. Construct the first deep neural network, which is used to measure the tissue area of ​​each lip gland in the digital pathological section of the lip gland one by one (mm 2 ), and add the area of ​​each lip gland tissue to get the total area of ​​lip gland tissue;

[0062] S2. Constructing a second deep neural network and a third deep neural network for identifying lymphocyte-dense areas, and statistically measuring the number of lymphocyte foci in the lip gland tissue to obtain the number of lymphocyte foci;

[0063] The definition of the lymphocyte focus is: the aggregation of more than 50 lymphocytes is defined as the lymphocyte focus;

[0064] S3. Using the data of the total area of ​​labial gland tissue and the number of lymphocyte foci, calculate the focal index;

[0065] The formula for cal...

Embodiment 2

[0089] Example 2: Intelligent analysis system for labial gland pathology

[0090] Based on the method of embodiment 1, a lip gland pathological intelligent analysis system includes a lip gland tissue area measurement module (1), a lymphocyte focus measurement module (3), an analysis processing module (6), and a result display module (7);

[0091] The system operation and the function of each module are as follows:

[0092] The labial gland tissue area measurement module (1) includes measuring the labial gland tissue area (mm 2 ) module, and the lip gland tissue area summary module, the lip gland tissue area summary module adds up the measured lip gland tissue areas to obtain the total lip gland tissue area;

[0093] The lymphocyte focus determination module (3) includes a lymphocyte focus identification module and a lymphocyte focus quantity summary module, which identifies and measures the lymphocyte focus quantity in the lip gland tissue, and transmits the result to the lym...

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Abstract

The invention discloses an intelligent analysis system and method for labial gland pathology. The system comprises a labial gland tissue area determination module, a lymphocyte lesion determination module, an analysis processing module and a result display module. According to the system, by constructing a first deep neural network, the area (mm<2>) of each labial gland tissue in a labial gland digital pathological section is measured one by one, and the area of each labial gland tissue is added to obtain the total area of the labial gland tissue; meanwhile, a second deep neural network and a third deep neural network are constructed for identifying and counting the number of lymphocyte lesions aggregated by more than 50 lymphocytes to obtain the number of the lymphocyte lesions; and further whether the patient meets the gold standard for diagnosing the sicca syndrome or not is calculated, that is, the focal index is greater than or equal to 1, so as to provide diagnosis suggestions for clinicians. The system realizes intelligent analysis and evaluation of the pathology of the labial gland, can directly output a judgment result, is simple and accurate, not only solves the clinical problem that an artificial labial gland pathology report is not standard, but also can promote the process of standardized diagnosis of the sicca syndrome in China.

Description

technical field [0001] The invention belongs to the field of medical technology. More specifically, it relates to an intelligent analysis system and method for evaluating labial gland pathology. Background technique [0002] Sjögren's syndrome is a common autoimmune connective tissue disease, which is a chronic disease. It occurs frequently in middle-aged and perimenopausal women. Elevated antibody levels and the involvement of multiple organ systems outside the glands based on vasculitis. In severe cases, important organs such as the kidney, liver, and lungs may be involved, and may even lead to the death of the patient. Sjogren's syndrome is a global disease, and the annual incidence rate per 100,000 people is as high as 6.0-11.8 in Asia, followed by Europe (3.9-5.3) and North America (3.9). The prevalence rate of the Chinese population is 0.33% to 0.77%, and the estimated number of patients is not less than 4 million. Sjogren's syndrome has its unique disease involveme...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/214G06F18/241Y02A90/10
Inventor 莫颖倩戴冽欧阳志明李谦华柳叶青
Owner SUN YAT SEN MEMORIAL HOSPITAL SUN YAT SEN UNIV
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