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Cervical cancer cell image recognizing algorithm based on convolutional neural network

A convolutional neural network, cervical cancer cell technology, applied in the field of medical image processing, can solve the problem that the results are not very reliable

Inactive Publication Date: 2018-08-03
HARBIN UNIV OF SCI & TECH
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  • Summary
  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

The result of the classifier is based on the statistics of the features. If the statistics of the features are wrong, the results will not be very reliable.

Method used

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  • Cervical cancer cell image recognizing algorithm based on convolutional neural network
  • Cervical cancer cell image recognizing algorithm based on convolutional neural network
  • Cervical cancer cell image recognizing algorithm based on convolutional neural network

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Embodiment Construction

[0019] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments; based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work , All belong to the protection scope of the present invention.

[0020] See figure 1 with figure 2 , The embodiments of the present invention include:

[0021] A cervical cancer cell image recognition algorithm based on convolutional neural network, including: data preparation stage, using a large target surface high-definition industrial camera with fast focus algorithm to collect and annotate cervical cell TCT images; for the collected cell image preprocessing stage, adopt The watershed algorithm locates the cel...

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Abstract

The invention discloses a cervical cancer cell image recognizing algorithm based on a convolutional neural network. In a traditional method, due to precise dividing and manual feature extracting and selecting of cytoplasms or cell nucleuses, once features with dividing errors or features not accurately extracted are generated, the cell recognizing accuracy can be reduced. By automatically extracting deep features in cell images through the convolutional neural network, a recognizing task is completed. The recognizing algorithm includes the steps of roughly dividing a cervical cell TCT image; secondly, inputting the roughly-divided image into a convolutional neural network model for training; thirdly, storing the trained network model to obtain a final recognizing result. The cervical cancer cell image recognizing algorithm is different from the traditional recognizing method and has a good recognizing effect in actual application.

Description

Technical field [0001] The invention relates to the technical field of medical image processing, in particular to a cervical cancer cell picture recognition algorithm based on a convolutional neural network. Background technique [0002] In the past decades, the identification of cervical cancer cells mainly includes three steps: cell (cytoplasm and nucleus) segmentation, feature extraction and cell classification. Cell segmentation algorithms include threshold-based segmentation methods and edge-based segmentation methods. Cell feature extraction generally extracts manual features that describe morphological and chromatin features, and then uses feature selection or dimensionality reduction algorithms to organize the resulting features for classification. Cell classification generally uses classifiers based on Bayesian rules or support vector machines for classification. [0003] However, due to the serious overlap of cells, the existing segmentation algorithms cannot accurately...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06K9/34G06N3/04
CPCG06V10/267G06N3/045G06F18/214
Inventor 黄金杰陆春宇王雅君
Owner HARBIN UNIV OF SCI & TECH
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