Repository logo
  • Log In
Repository logo
  • Communities & Collections
  • All of DORA
  • Log In
  1. Home
  2. Browse by Author

Browsing by Author "Cindy, N."

Now showing 1 - 1 of 1
Results Per Page
Sort Options
  • Loading...
    Thumbnail Image
    ItemOpen Access
    A case study of image retrieval on lung cancer chest x-ray pictures.
    (IEEE, 2008) Gile Narcisse Fanzou, T.; Ning, W.; Cindy, N.; Siewe, Francois; Xudong, L.; De, X.
    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.
Quick Links
  • De Montfort University Home
  • Library Learning Services
  • DMU Figshare (DMU's Data Repository)
Useful Links
  • Submission Guide
  • DMU Open Access Libguide
  • Take Down Policy
  • Connect with DORA

Kimberlin Library

De Montfort University
The Gateway
Leicester, LE1 9BH
0116 257 7042
justask@dmu.ac.uk

DSpace software copyright © 2002-2025 LYRASIS

  • Cookie settings
  • Privacy policy
  • End User Agreement
  • Send Feedback