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Automatic chromosome classification method and classifier based on convolutional neural network

A convolutional neural network and automatic classification technology, applied in the field of chromosome automatic classification method and classifier based on convolutional neural network, can solve problems such as large workload and low work efficiency, achieve good performance, increase accuracy, improve The effect of generalization ability

Inactive Publication Date: 2019-10-29
BEIHANG UNIV +1
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Problems solved by technology

This traditional method has high requirements on the experience and professionalism of doctors or staff, and requires manual operation by doctors and direct visual recognition, which leads to heavy workload and low work efficiency.

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  • Automatic chromosome classification method and classifier based on convolutional neural network
  • Automatic chromosome classification method and classifier based on convolutional neural network
  • Automatic chromosome classification method and classifier based on convolutional neural network

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Embodiment Construction

[0022] The present application will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0023] In the following introduction, the terms "first" and "second" are only used for the purpose of description, and should not be understood as indicating or implying relative importance. The following introduction provides multiple embodiments of the present disclosure, and different embodiments can be replaced or combined and combined, so the application can also be considered to include all possible combinations of the same and / or different embodiments described. Thus, if one embodiment contains features A, B, C, and another embodiment contains features B, D, then the application should also be considered to include all other possible combinations containing one or more of A, B, C, D Although this embodiment may not be clearly written in the following content.

[0024] In order to make the purpose, technical solution and advantages of...

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Abstract

The invention provides an automatic chromosome classification method and classifier based on a convolutional neural network. Based on a classifier of the convolutional neural network, a data driving method is utilized, a large number of features do not need to be extracted manually any more, the classifier based on the convolutional neural network can automatically extract rich features from massdata, the trouble of feature engineering is avoided, and the richness of feature extraction is improved. The purpose of improving the accuracy of the classification result is effectively achieved by automatically extracting massive features. Due to the fact that the convolutional neural network used in the experiment has the characteristics of local receptive field and weight sharing, the generalization ability of the network is improved, and the purpose that the convolutional neural network has better performance is achieved.

Description

technical field [0001] The present disclosure relates to the technical field of artificial intelligence, in particular, to an automatic chromosome classification method and a classifier based on a convolutional neural network. Background technique [0002] Humans have a total of 46 chromosomes, including 22 pairs of autosomes, X and Y chromosomes. Both autosomes and sex chromosomes carry genetic factors, which control hereditary traits and the level of physiological functions of the human body. Because human genetic material is carried by chromosomes, abnormalities in chromosomes can lead to many fatal diseases and birth defects. Chromosomal abnormalities are mainly divided into two situations, one is abnormal number of chromosomes, which is called chromosome number aberration; the other is abnormal chromosome structure, where there are deletions, duplications, insertions, translocations or inversions of chromosomes, which is called Chromosomal aberrations. Diseases cause...

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Application Information

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IPC IPC(8): G06K9/00
CPCG06V20/695G06V20/698
Inventor 万涛许静阴赪宏衣正阳王一鹏岳文涛
Owner BEIHANG UNIV
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