Image processing techniques for bone image analysis

Author

Liu, Zhi-Qiang ; Austin, Timothy J. ; Moore, Daniel

Author_Institution

Dept. of Comput. Sci., Melbourne Univ., Parkville, Vic., Australia

Volume

1

fYear

1995

fDate

23-26 Oct 1995

Firstpage

458

Abstract

Features of human bones are useful to establish correlation between bone structure and age, and information about age-related bone diseases. This paper presents a new approach to quantitative analysis of cross sections of human bones using image processing techniques. The system uses the adaptive neighborhood algorithm, clustering, local covariance measures, and the fuzzy region growing algorithm. The system extracts various bone features with consistency and provides more reliable statistics. As a result, the authors are able to correlate bone features with age and possibly with age related bone diseases such as osteoporosis

Keywords

adaptive signal processing; bone; feature extraction; medical image processing; adaptive neighborhood algorithm; age-related bone diseases; bone age; bone image analysis; bone structure; fuzzy region growing algorithm; human bone cross sections; image processing techniques; local covariance measures; osteoporosis; quantitative analysis approach; reliable statistics; Adaptive systems; Bone diseases; Clustering algorithms; Data mining; Feature extraction; Fuzzy systems; Humans; Image analysis; Image processing; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1995. Proceedings., International Conference on

Conference_Location

Washington, DC

Print_ISBN

0-8186-7310-9

Type

conf

DOI

10.1109/ICIP.1995.529745

Filename

529745