基于卷积神经网络的染色体核型分析方法研究进展

Research Progress of Chromosome Karyotype Analysis Based on Convolution Neural Network

染色体核型分析技术是细胞遗传学中用于分析染色体图像的一项重要方法,在遗传病诊断和肿瘤物理学研究中具有重要意义,这个特点使之成为一个热门的研究方向。近年来,通过神经网络的方法进行的染色体核型分析任务在分析准确度上的显著提升引起学者们的广泛关注。通过对使用神经网络进行核型分析的研究方法进行分析和归纳,为基于卷积神经网络的核型分析方法的进一步研究提供理论基础。

Chromosomal karyotype analysis is an important method used to analyze chromosome images in cytogenetics and has great significance in genetic disease diagnosis and tumor physics research.This makes it a hot research direction.In recent years,the accuracy of chromosome karyotype analysis based on neural network has been greatly improved,which has attracted much more attention of scholars.Analyzes and summarizes the research methods of karyotype analysis using neural network,which provides a theoretical basis for the further study of the method of karyotype analysis based on convolutional neural network.