建设适应重庆地区的区域医学影像信息和大数据分析平台

doi:10.13523/j.cb.20171105

中国生物工程杂志

2017, Vol. 37

Issue (11): 28-36 DOI: 10.13523/j.cb.20171105

计算生物学与生物信息学专栏

建设适应重庆地区的区域医学影像信息和大数据分析平台

肖铭¹, 陈平², 何鸿谕², 章乐¹

1. 西南大学计算机与信息科学学院重庆 400700;
2. 重庆市中迪医疗信息科技股份有限公司重庆 401320

Development of the Chongqing Regional Medical Imaging Information and Big Data Analysis Platform

XIAO Ming¹, CHEN Ping², HE Hong-yu², ZHANG Le¹

1. School of Computer and Information Science, Southwest University, Chongqing 400700, China;
2. Zdmedical, Information Polytron Technologies Inc in Chongqing, Chongqing 401320, China

全文: PDF(2333 KB) HTML

摘要： 由于重庆地区的医疗水平参差不齐，所以建设重庆地区区域医疗影像信息化系统，实现各类影像信息共享，对提供高效的医疗卫生服务具有非常重要的意义。目前，建设重庆地区区域医疗影像交互平台面临着整体设计集成程度和扩展性不高、医学影像标准不统一、数据安全与质量标准不完整、平台没有整合大数据分析挖掘方法等问题。为此，首先对重庆地区区域影像平台的整体结构进行了设计，提出了区域影像交互平台的五层体系结构；其次在五层体系结构基础上制定和加强了影像数据标准和信息安全体系；并且在区域影像中心的基础上，嵌入了医学影像大数据分析工具。应用结果证明，交互平台具有较高的集成程度和扩展性，平台标准的制定和加强能有效的提高交互效率，加强数据安全和质量管理，并且平台可对海量数据进行有效的分析。

关键词： 数据挖掘; 信息安全; 区域信息化; 影像交互平台; 大数据分析

Abstract: It is very important and necessary to develop the regional medical imaging information system to share the various type of the imaging information and provide an efficient medical health service in Chongqing area due to Chongqing's uneven medical level. At present, there are several existing problems for the development of the Chongqing's regional medical imaging information platform. For example, the system integration is not enough, the medical imaging standards are not uniform, data security and quality standards are not complete and the platform does not integrate the big data analysis methods and so on. For these reasons, this study designs the structure of the regional medical imaging information platform in Chongqing area, and puts forward the regional imaging interactive platform with five layer architecture. Secondly, based on the five layer architecture, it establishes and strengthens the imaging data standards and information security system. Also, it integrates the medical imaging big data analysis tools into the established the big imaging data center. The study demonstrates that the platform is not only highly integrated and scalability, but also has efficient interactive capacity as well as high data security and quality standards, because of the development and strengthen of the platform standards. Finally, the platform can efficiently analyze the big imaging data.

Key words: Big data analysis Information security Regional information Imaging interactive platform Data mining

收稿日期: 2017-09-26 出版日期: 2017-11-15

ZTFLH:

TP399

基金资助: 国家自然科学基金（6137213）、重庆杰出青年基金（cstc2014jcyjjq40003）、中央高校业务经费（XDJK2014B012，XDJK2016A003）资助项目

通讯作者: 陈平, 章乐 E-mail: 15013071@qq.com;zhangle06@scu.edu.cn

	服务
	把本文推荐给朋友
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	肖铭
	何鸿谕
	陈平
	章乐

引用本文:

肖铭, 陈平, 何鸿谕, 章乐. 建设适应重庆地区的区域医学影像信息和大数据分析平台[J]. 中国生物工程杂志, 2017, 37(11): 28-36.

XIAO Ming, CHEN Ping, HE Hong-yu, ZHANG Le. Development of the Chongqing Regional Medical Imaging Information and Big Data Analysis Platform. China Biotechnology, 2017, 37(11): 28-36.

链接本文:

https://manu60.magtech.com.cn/biotech/CN/10.13523/j.cb.20171105 或 https://manu60.magtech.com.cn/biotech/CN/Y2017/V37/I11/28

[1]	Clark T. PACS and imaging informatics:basic principles and applications. Biomedical Instrumentation and Technology, 2006, 40(2):125.
[2]	Kaihara S. The present and future of medical information system:in relation to hospital pharmacy. Journal of the Nippon Hospital Pharmacists Association, 1989, 15(5):319-325.
[3]	闫龑. 国家卫计委发布远程医疗系统建设统一技术指南. 医学信息学杂志, 2015(1):94-95. Yan Y. National health planning commission issued a unified technical guideline for telemedicine system construction, Journal of Medical Informatics, 2015(1):94-95.
[4]	重庆市卫生和计划生育委员会. 2015年重庆市卫生统计年报分析报告.. http://www.cqcha.com.cn/upfiles/201605/20160510090435392.pdf. Chongqing Health and Planned Parenthood Commission. Analysis report of Chongqing health statistics in 2015.. http://www.cqcha.com.cn/upfiles/201605/20160510090435392.pdf.
[5]	吴福理, 张彤,梁荣华, 等. 基于云平台的医学影像可视交互平台. 中国科学:信息科学, 2014, 44(11):1432-1444. Wu F L, Zhang T, Liang R H, et al.Visual interactive platform for medical images based on cloud platform. Chinese Science:Information Science, 2014,44(11):1432-1444.
[6]	张翼, 张大鹏, 刘孔超,等. 基于医疗信息交互技术的区域医学影像平台构建. 中国数字医学, 2016, 11(7):100-102. Zhang Y, Zhang D P, Liu K C et al.Construction of Regional Medical Imaging Integrating System Based on HIE Technology. China Digital Medicine.2016,11(7):100-102.
[7]	Kaelber D C, Bates D W. Health information exchange and patient safety. Journal of Biomedical Informatics, 2007, 40(6 Suppl):40-45.
[8]	Henderson M, Behlen F M, Parisot C, et al. Integrating the healthcare enterprise:a primer. Part 4. The role of existing standards in IHE. Radiographics A Review Publication of the Radiological Society of North America Inc, 2001, 21(6):1597-1603.
[9]	Mildenberger P, Eichelberg M, Martin E. Introduction to the DICOM standard. European Radiology, 2002, 12(4):920-922.
[10]	Bidgood W D, Horii S C, Prior F W, et al. Understanding and using DICOM, the data interchange standard for biomedical imaging. Journal of the American Medical Informatics Association Jamia, 1997, 4(3):199-212.
[11]	Haak D, Page C E, Reinartz S, et al. DICOM for clinical research:PACS-integrated electronic data capture in multi-center trials. Journal of Digital Imaging, 2015, 28(5):1-9.
[12]	Sayed-Abbassi B. DICOM data from a data warehouse design perspective//AMCIS 2009 Proceedings. California:DBLP, 2009:34-36.
[13]	丁莹, 杨华民, 李文辉, 等. 分布式医学影像分析与处理平台的设计与实现.计算机工程与应用, 2008, 44(34):9-14. Ding Y, Yang H M,Li W H, et al. Design and implement of distributing medical imaging analyzing and processing platform DMIP. CEA, 2008, 44(34):9-14.
[14]	Iii U A E, Rhinehart E J, Rosemary A M, et al. Data communication and control for medical imaging systems:WO, US6970735. 2005.
[15]	Wang S, Pavlicek W, Roberts C C, et al. An automated DICOM database capable of arbitrary data mining (including radiation dose indicators) for quality monitoring. Journal of Digital Imaging, 2011, 24(2):223.
[16]	吴辉群, 翁霞, 王磊, 等. 医学影像大数据的存储与挖掘技术研究. 中国数字医学, 2016, 11(2):2-6. Wu H Q, Weng X, Wang L, et al. Study on big medical imaging data storage and mining techniques. China Digital Medicine.2016,11(2):2-6.
[17]	Antonie M L, Osmar R Z, Coman A. Application of data mining techniques for medical image classification//Proceeding of Second International Workshop on Multimedia Data Mining. San Francisco, 2001:94-101.
[18]	Hsu W, Lee M L,Goh K G, Image mining in IRIS:integrated retinal information system. Acm Sigmod Record, 2000, 29(2):593-593.
[19]	Megalooikonomou V, Davatzikos C, Herskovits E H. Mining lesion-deficit associations in a brain image database//ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. San Diego:ACM, 1999:347-351.
[20]	孙磊, 胡学龙, 张晓斌, 等. 生物医学大数据处理的云计算解决方案. 电子测量与仪器学报, 2014(11):1190-1197. Sun L, Hu X L, Zhang X B, et al.Cloud computing solutions for processing biomedical data. Journal of Electronic Measurement and Instrumentation. 2014(11):1190-1197.
[21]	范炜玮, 赵东升,王松俊, 等. 基于云计算的区域医疗信息共享平台的设计与实现. 军事医学, 2015(4):257-260. Fan W W, Zhao D X, Wang S J, et al. A cloud computing-based implementation of regional medical information sharing. Military Medical Sciences. 2015(4):257-260.
[22]	孙雪梅, 区域医疗影像诊断中心的建设方案探讨. 中国医疗设备, 2016, 31(4):97-99. Sun X M. Discussion on the construction of regional medical imaging diagnosis center. China Medical Devices. 2016, 31(4):97-99.
[23]	范晨皓, 何萍. 基于分布式存储的区域医疗影像系统建设. 中国数字医学, 2014(1):58-61. Fan C H, He P. The Construction of regional medical imaging system based on the distributed storage. China Digital Medicine. 2014(1):58-61.
[24]	Gibaud B. The quest for standards in medical imaging. European Journal of Radiology, 2011, 78(2):190-198.
[25]	王斌君. 信息安全体系. 北京:高等教育出版社, 2008:56-60. Wang B J. Information Security System. Beijing:Higher Education Press, 2008:56-60.
[26]	张建标, 赖英旭, 侍伟敏, 等.信息安全体系结构, 北京:北京工业大学出版社,2011:76-88. Zhang J B, Lai Y X, Shi W M, et al. Information Security Architecture. Beijing:Beijing University of Technology Press, 2011:76-88.
[27]	Freier A,Karlton P, Kocher P. The SSL protocol version 3.0. Nano Letters, 1996, 11(2):148-149.
[28]	韩家炜, 坎伯,裴健, 等. 数据挖掘概念与技术. 第二版. 北京, 机械工业出版社,2006:114-116. Han J W, Micheline K, Jian P, et al. Data mining:concepts and techniques. 2nd ed. Beijing:China Machine Press, 2006:114-116.
[29]	Pawlak Z. Rough set. International Journal of Computer & Information Sciences, 1982, 11(5):341-356.
[30]	Kohavi R. The power of decision tables//European Conference on Machine Learning. Springer-Verlag, 1995:174-189.
[31]	Kryszkiewicz M. Rough set approach to incomplete information systems. Information Sciences, 1998, 112(1-4):39-49.
[32]	王国胤, 姚一豫,于洪, 粗糙集理论与应用研究综述. 计算机学报, 2009,32(7):1229-1246. Wang G Y, Yao Y Y, Yu H. A survey on rough set theory and applications. Chinese Journal of Computers, 2009,32(7):1229-1246.
[33]	吕林涛, 王鹏, 李军怀, 等. 基于时间序列的趋势性分析及其预测算法研究. 计算机工程与应用, 2004,40(19):172-174. Lv L T, Wang P, Li J H, et al. Research on the trend analysis and predictive algorithm based on time series. Computer Engineering and Applications, 2004, 40(19):172-174.
[34]	Keogh E, Chakrabarti K, Pazzani M, et al. Dimensionality reduction for fast similarity search in large time series databases. Knowledge & Information Systems, 2001, 3(3):263-286.
[35]	Keogh E, Kasetty S. On the need for time series data mining benchmarks:asurvey and empirical demonstration. Data Mining & Knowledge Discovery, 2003,7(4):349-371.
[36]	贾澎涛, 何华灿, 刘丽, 等. 时间序列数据挖掘综述. 计算机应用研究, 2007, 24(11):15-18. Jia P T, He H C, Liu L, et al. Overview of time series data mining. Application Research of Computers, 2007, 24(11):15-18.
[37]	Xin Y U, Deng W D, Peng J S. A rough set approach to incomplete information systems. Computer Engineering & Science, 2005, 112(4):39-49.

[1]	尤元海张建中. 基因表达谱芯片的数据挖掘[J]. 中国生物工程杂志, 2009, 29(10): 87-91.
[2]	余海浪,马文丽,郑文岭. 用于基因数据挖掘的基因表达数据库GEO[J]. 中国生物工程杂志, 2007, 27(8): 96-103.
[3]	杨仑,夏振华,陈剑,毛颖,徐朗莱. 中国基因专利的数据挖掘[J]. 中国生物工程杂志, 2006, 26(11): 91-96.

Viewed

Full text

Abstract

Cited

Shared

Discussed