Segmentation of medical images using geo-theoretic distance matrix in fuzzy clustering

Author

Pham, Tuan D. ; Eisenblätter, Uwe ; Golledge, Jonathan ; Baune, Bernhard T. ; Berger, Klaus

Author_Institution

Sch. of Inf. Technol. & Electr. Eng., Univ. of New South Wales at ADFA, Canberra, ACT, Australia

fYear

2009

fDate

7-10 Nov. 2009

Firstpage

3369

Lastpage

3372

Abstract

Investigation on novel methods for extracting objects of interest in medical images has been an important and challenging area of research in image analysis. In particular, medical images are highly spatially correlated and subject to fuzzy distribution of pixels, we present in this paper a new algorithm for medical image segmentation with special reference to abdominal aortic aneurysm and degraded human brain imaging. Development of the new algorithm is based on the implementation of the theoretic distance matrix with spatial semi-variances.

Keywords

computerised tomography; fuzzy set theory; image segmentation; matrix algebra; medical image processing; pattern clustering; CT imaging; abdominal aortic aneurysm; degraded human brain imaging; fuzzy clustering; geo-theoretic distance matrix; medical image segmentation; Abdomen; Aneurysm; Biomedical imaging; Brain; Clustering algorithms; Degradation; Humans; Image analysis; Image segmentation; Pixel; CT imaging; MRI; Medical image segmentation; fuzzy c-means; semi-variance;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing (ICIP), 2009 16th IEEE International Conference on

Conference_Location

Cairo

ISSN

1522-4880

Print_ISBN

978-1-4244-5653-6

Electronic_ISBN

1522-4880

Type

conf

DOI

10.1109/ICIP.2009.5413877

Filename

5413877