Cell labeling system and method

A cell and cell classification technology, applied in the field of computer medicine, can solve the problems of tedious labeling work and taking up a lot of time

Active Publication Date: 2020-06-23
SOUTH CHINA NORMAL UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Labeling bone marrow cells requires professional inspectors, and the labeling work is cumbersome and takes a lot of time. Therefore, a system and method for quickly labeling bone marrow cells is needed

Method used

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  • Cell labeling system and method
  • Cell labeling system and method

Examples

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Embodiment 1

[0051] This example provides a method for labeling bone marrow cells. There are various types of nucleated cells in bone marrow. There are as many as 49 types of nucleated cells commonly used in clinical examinations. There are many nucleated cells in bone marrow that are not common but have clinical value. More than 263 categories. In different patients, different thickness of smears, different regions and specimens with different staining, the variation of cell size and shape is relatively large. The method of manual classification and counting requires inspectors to have long-term work experience and technical proficiency to make high-quality inspection reports. At present, the work efficiency of manual microscopic inspection is low, and many hospitals have the phenomenon of lack of morphological inspection personnel and faults. . Using the method of the present invention to mark bone marrow cells can verify the accuracy and reliability of the method of the present inventi...

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Abstract

The invention provides a cell labeling system and method. The method comprises the following steps: acquiring a cell image; manually labeling position information of all cells in the series of cell images to form a training set of a cell detection model, and training the cell detection model by adopting the training set; taking a pre-training model based on a large number of image data sets as a cell classification model; carrying out cell labeling on the to-be-labeled cell image by utilizing the two models; results are corrected in a manual labeling mode, when the corrected data volume of thetwo models reaches a threshold value, fine adjustment training is started to be conducted on the two models, the trained models are adopted for detection, and the process is cycled. According to thecell labeling system, the labeling process and function are designed according to the labeling requirement of a training sample needed by cell detection, particularly, the labeling device and the labeling model training device are designed, model training is conducted on the basis of manually labeling a small number of cells, automatic labeling with high accuracy can be achieved, and the cell labeling efficiency is greatly improved.

Description

technical field [0001] The invention relates to the technical field of computer medicine, in particular to a cell labeling system and method. Background technique [0002] Microscopic examination of bone marrow cells is one of the key diagnostic methods in hematology. It is often used to diagnose a variety of diseases, including leukemia, multiple myeloma, lymphoma, anemia and pancytopenia. At present, manual microscopic examination is still the main diagnostic method. From getting the stained specimen smear to generating the bone marrow cell inspection report, one of the key links is to observe the evenly distributed area around the smear bone marrow granules under the oil microscope, and use bow-shaped or battlement-shaped mobile counting to classify 200 nucleated cells. cells, and record the results on a paper nucleated cell sorting sheet or a cell counter while observing the sort. There are various types of nucleated cells in bone marrow. There are as many as 49 types ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/698G06F18/214
Inventor 马琼雄黄德豪黄佩铎佘成隆汤盛钧赵星宇黄婷炜秦子雨张庆茂郭亮
Owner SOUTH CHINA NORMAL UNIVERSITY
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