Classification of X-ray images using grid approach

Bertalya, Prihandoko, Djati Kirani, Maulana Tb Kusuma

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

The process of medical image classification is still carried out manually using the knowledge of the physician or radiologist, which leads to inaccurate and slow process of object identification. Thus, we need an automatic system that can classify medical images, accurately and faster from query images into one of the pre-defined classes. In this research, we are dealing with the classification of medical image to the image classes that are defined in the database. We focus on managing the shape of X-ray image to perform the classification process and use the Euclidean distance and Jeffrey Divergence techniques to obtain image similarity. We use Freeman Code to represent the shape of X-ray images. This paper shows the development of the Freeman Code representation by simplifying the shape of X-ray image conducts to obtain the best recognition rate.

Original languageEnglish
Title of host publicationSITIS 2008 - Proceedings of the 4th International Conference on Signal Image Technology and Internet Based Systems
Pages314-319
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2008
Event4th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2008 - Bali, Indonesia
Duration: 30 Nov 20083 Dec 2008

Publication series

NameSITIS 2008 - Proceedings of the 4th International Conference on Signal Image Technology and Internet Based Systems

Conference

Conference4th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2008
CountryIndonesia
CityBali
Period30/11/083/12/08

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