A case study of Image Retrieval on Lung cancer chest X-ray pictures

摘要：

This paper presents a case study of an image retrieval system based on a notion of similarity between images in a multimedia database and where a user request can be an image file or a keyword.The CBIR (Content Based Image Retrieval) system,the current System of Search for Information (SSI) --e.g.PEIR,MIRC,MIR,IRMA,and Pathopic--and the Current Search Engines (CSE) --e.g.Google,Yahoo and Alta Vista--make image search possible only when the query is a keyword.This type of search is limited because keywords are not expressive enough to describe all important characteristics of an image.For example,an exact match request cannot be formulated in such systems and in SSI system,users should know natural language (e.g.English,French or German) used.We used XIRS (an XML Image Retrieval System) to set up a similarity distance between images,then to compare the request image with those in a database.An experimentation of XIRS on lung cancer diagnosis is presented.The statistics show that our system is more efficient than leading CBIR systems such as ERIC7,PEIR,PathoPic and CSE.

关键词： XML Image retrieval similarity search diagnosis web Medical Information systems

作者: Gile Narcisse Fanzou T. Wang Ning Nathalie Cindy K. Fran(c)ois Siewe Lin Xudong Xu De

作者单位: School of Computer & Information Technology Beijing Jiaotong University 100044 Beijing China Department of Computer Science University of Yaoundé 1812 Yaoundé Cameroon Software Technology Research Laboratory School of Computing De Montfort University Leicester LE1 9BH

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）