DocumentCode :
640983
Title :
Fuzzy texture descriptors for early diagnosis of osteoarthritis
Author :
Chetty, Girija ; Scarvell, Jennie ; Mitra, Subhasish
Author_Institution :
Fac. of ESTeM, Univ. of Canberra, Canberra, ACT, Australia
fYear :
2013
fDate :
7-10 July 2013
Firstpage :
1
Lastpage :
6
Abstract :
Knee osteoarthritis (OA) is a debilitating health condition affecting elderly population. Early diagnosis of the disease noninvasively will be very useful, and requires novel image analysis techniques to be developed for processing radiological and MRI scans of knee joints. In this paper, we propose novel micro texture based feature descriptors for modeling subtle variations in MRI T2 maps, so as to facilitate early detection of osteoarthritis. The experimental evaluation of the proposed micro texture descriptors on a publicly available OAI database show, that the proposed features allow a significant improvement in discriminating the textures for MRI T2 maps, corresponding to normal subjects as compared to the subjects with risk factors for developing osteoarthritis.
Keywords :
biomedical MRI; diseases; feature extraction; fuzzy set theory; image texture; medical image processing; MRI T2 maps; MRI scan; OAI database; disease diagnosis; elderly population; fuzzy texture descriptor; health condition debilitation; image analysis technique; knee joints; micro texture based feature descriptor; osteoarthritis detection; osteoarthritis diagnosis; radiological processing; Biomarkers; Databases; Feature extraction; Histograms; Magnetic resonance imaging; Osteoarthritis; Fuzzy Logic; Image Analysis; Osteoarthritis; Texture Descriptors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems (FUZZ), 2013 IEEE International Conference on
Conference_Location :
Hyderabad
ISSN :
1098-7584
Print_ISBN :
978-1-4799-0020-6
Type :
conf
DOI :
10.1109/FUZZ-IEEE.2013.6622439
Filename :
6622439
Link To Document :
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