A method and system for automatic chromosome analysis based on depth learning

An automatic analysis system and deep learning technology, applied in the field of automatic chromosome analysis methods and systems based on deep learning, can solve problems such as unstable confusion, decreased classification accuracy, and low chromosome recognition rate, and achieve improved classification accuracy , the effect of utilizing sufficient and high generalization capabilities

Active Publication Date: 2019-02-15
HUAQIAO UNIVERSITY
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Problems solved by technology

Restricted by the depth of striped feature extraction and feature set selection, the chromosome recognition rate of the current scheme is low, especially for overlapping chromosomes with missing striped information, the

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  • A method and system for automatic chromosome analysis based on depth learning
  • A method and system for automatic chromosome analysis based on depth learning
  • A method and system for automatic chromosome analysis based on depth learning

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[0057] The present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. In particular, the following examples are only used to illustrate the present invention, but not to limit the scope of the present invention. Likewise, the following embodiments are only some but not all embodiments of the present invention, and all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0058] The invention provides an automatic chromosome analysis method based on deep learning, which can adopt the chromosome segmentation method based on deep learning, does not rely on specific chromosome morphological patterns, has high generalization ability, and can adopt the chromosome classification method based on deep learning, taking into account Chromosome global shape and banding features, improve classification accuracy, can adopt multi-s...

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Abstract

The invention discloses a chromosome automatic analysis method and a chromosome automatic analysis system based on depth learning, which can adopt multi-level processing, stratify the independent formand overlapping form of chromosomes, and perform cluster analysis on chromosome position coordinates, classification labels and classification confidence to output a karyotype map. In this manner, the method of chromosome segmentation based on depth learning can be adopted, independent of specific chromosomal morphological patterns, The method has high generalization ability, can adopt chromosomeclassification method based on depth learning, take into account the global morphology and banding characteristics of chromosomes, improve classification accuracy, can adopt multi-scale processing, more fully utilize the detected images, and effectively improve the segmentation effect in the case of chromosome overlap and adhesion.

Description

technical field [0001] The invention relates to the technical field of chromosome analysis, in particular to an automatic chromosome analysis method and system based on deep learning. Background technique [0002] Human chromosome identification is an important research topic in medical genetics. It has a wide range of applications in the fields of medical clinical diagnosis, auxiliary teaching and scientific research. It is an important basis for judging human genetic diseases. Traditional chromosome identification is done manually, not only the identification process is cumbersome, but also the identification work is prone to errors. In order to reduce the workload of medical staff and medical teaching staff and improve the identification efficiency, the automatic identification of chromosomes using computer image processing technology has been used. [0003] Chromosome automatic recognition technology mainly includes three processes: image preprocessing, image segmentati...

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Application Information

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IPC IPC(8): G06K9/62G06T7/00G06T7/136
CPCG06T7/0012G06T7/136G06T2207/10024G06T2207/20081G06T2207/20084G06F18/241G06F18/214
Inventor 杜吉祥柳昊良张洪博雷庆杨秀红
Owner HUAQIAO UNIVERSITY
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