A deep learning method and device for bone marrow imaging cell detection

doi:10.21037/atm-22-486

	A deep learning method and device for bone marrow imaging cell detection
	Liu, Jie 1; Yuan, Ruize 2,3; Li, Yinhao 2,3; Zhou, Lin 1; Zhang, Zhiqiang 4; Yang, Jidong 4; Xiao, Li 2,3,5
	2022-02-01
发表期刊	ANNALS OF TRANSLATIONAL MEDICINE
ISSN	2305-5839
卷号	10 期号:4 页码:11
摘要	Background: Morphological analysis of bone marrow cells is considered as the gold standard for the diagnosis of leukemia. However, due to the diverse morphology of bone marrow cells, extensive experience and patience are needed for morphological examination. automatic diagnosis system through the comprehensive application of image analysis and pattern recognition technology is urgently needed to reduce work intensity, error probability and improves work efficiency. Methods: In this article, we establish a new morphological diagnosis system for bone marrow cell detection based on the deep learning object detection framework. The model is based on the Faster Region-Convolutional Neural Network (R-CNN), a classical object detection model. The system automatically detects bone marrow cells and determines their types. As specimens have severe long-tail distribution, i.e., the frequency of different types of cells varies dramatically, we proposed a general score ranking loss to solve such a problem. The general score ranking loss considers the ranking relationship between positive and negative samples and optimizes the positive sample with a higher classification probability value. Results: We verified this system with 70 bone marrow specimens of leukemia patients, which proved that it can realize intelligent recognition with high efficiency. The software is finally integrated into the microscope system to build an augmented reality system. Conclusions: Clinical tests show that the response speed of the newly developed diagnostic system is faster than that of trained diagnostic experts.
关键词	Morphological analysis diagnosis of leukemia deep learning object detection
DOI	10.21037/atm-22-486
收录类别	SCI
语种	英语
资助项目	National Science Foundation of China[31900979] ; CCFTencent Open Fund ; 2019 Medical Big Data and Artificial Intelligence RD Project[2019MBD-048]
WOS研究方向	Oncology ; Research & Experimental Medicine
WOS类目	Oncology ; Medicine, Research & Experimental
WOS记录号	WOS:000766140700049
出版者	AME PUBL CO
引用统计	被引频次：7[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/18961
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Xiao, Li
作者单位	1.Chinese Peoples Liberat Army Gen Hosp, Med Ctr 7, Dept Lab, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing, Peoples R China 4.Hanyuan Pharmaceut Co Ltd, Beijing, Peoples R China 5.Univ Chinese Acad Sci, Ningbo Huamei Hosp, Ningbo, Peoples R China
推荐引用方式 GB/T 7714	Liu, Jie,Yuan, Ruize,Li, Yinhao,et al. A deep learning method and device for bone marrow imaging cell detection[J]. ANNALS OF TRANSLATIONAL MEDICINE,2022,10(4):11.
APA	Liu, Jie.,Yuan, Ruize.,Li, Yinhao.,Zhou, Lin.,Zhang, Zhiqiang.,...&Xiao, Li.(2022).A deep learning method and device for bone marrow imaging cell detection.ANNALS OF TRANSLATIONAL MEDICINE,10(4),11.
MLA	Liu, Jie,et al."A deep learning method and device for bone marrow imaging cell detection".ANNALS OF TRANSLATIONAL MEDICINE 10.4(2022):11.