[1]孙凯,姚旭峰,马风玲,等.基于机器学习的血细胞分类研究进展[J].中国医学物理学杂志,2020,37(1):127-132.[doi:DOI:10.3969/j.issn.1005-202X.2020.01.023]
 SUN Kai,YAO Xufeng,et al.Blood cell classification based on machine learning[J].Chinese Journal of Medical Physics,2020,37(1):127-132.[doi:DOI:10.3969/j.issn.1005-202X.2020.01.023]
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基于机器学习的血细胞分类研究进展()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
37
期数:
2020年第1期
页码:
127-132
栏目:
其他(数字医学等)
出版日期:
2020-01-10

文章信息/Info

Title:
Blood cell classification based on machine learning
文章编号:
1005-202X(2020)01-0127-06
作者:
孙凯12姚旭峰2马风玲12赵文硕12黄钢2
1.上海理工大学医疗器械与食品学院, 上海 200082; 2.上海健康医学院医学影像学院, 上海 200120
Author(s):
SUN Kai1 2 YAO Xufeng2 MA Fengling1 2 ZHAO Wenshuo1 2 HUANG Gang2
1. School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200082, China; 2. College of Medical Imaging, Shanghai University of Medicine & Health Sciences, Shanghai 200120, China
关键词:
机器学习图像处理分类血液细胞
Keywords:
Keywords: machine learning image processing classification blood cell
分类号:
R318;R329.2
DOI:
DOI:10.3969/j.issn.1005-202X.2020.01.023
文献标志码:
A
摘要:
基于机器学习的血细胞分类方法已经引起了人们的广泛重视。本文探讨了近几年基于机器学习的血液细胞分类领域的相关研究成果与进展,对目前各种研究所用到的数据采集、图像预处理、图像分割、特征提取及分类器分类方法所用新技术做出详细的说明与分析。深度学习在机器学习基础上发展而成,因其端到端、高准确度等优势展现出强大发展前景。目前研究趋向于采取深度学习与人工特征提取结合、改进网络结构等新方法不断提高网络模型分类准确度及泛化性。然而,基于机器学习的血细胞分类技术投入临床使用仍存在一些问题与挑战。
Abstract:
The study of machine learning (ML) for blood cell classification has aroused the interests of many researchers. In this paper, we summarized the recent development of ML algorithms for blood cell classification. The reviewed ML algorithms mainly consisted of data acquisition, image prepossessing, image segmentation, feature extraction and classification. Derived from traditional ML algorithms, the deep learning (DP) algorithms for blood cell classification have demonstrated strong prospects for presenting the advantages of high accuracy and more reliability. Till now, the topics of DP methods focuses on the aspects of extraction of artificial feature, design of learning networks, etc. This would aims to improve the accuracy of classification and generalization of DP models. However, ML classification of blood cells still have some challenges for clinical applications.

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备注/Memo

备注/Memo:
【收稿日期】2019-06-26 【基金项目】国家自然科学基金(61971275, 81830052);上海市教委项目(上海市政II类高原学科, 上海健康医学院, 2018-2020);上海市分子影像学重点实验室项目(18DZ2260400) 【作者简介】孙凯,在读硕士研究生,主要从事医学图像处理与分析,E-mail: 745757764@qq.com 【通信作者】姚旭峰,博士,教授,E-mail: yao6636329@hotmail.com
更新日期/Last Update: 2020-01-14