DocumentCode :
2857217
Title :
Watershed segmentation of high resolution magnetic resonance images of articular cartilage of the knee
Author :
Ghosh, Srinka ; Beuf, Olivier ; Ries, Michael ; Lane, Nancy E. ; Steinbach, Lynne S. ; Link, Thomas M. ; Majumdar, Sharmila
Author_Institution :
Bioeng. Graduate Group, San Francisco Univ., Berkeley, CA, USA
Volume :
4
fYear :
2000
fDate :
2000
Firstpage :
3174
Abstract :
High-resolution in-vivo Magnetic Resonance Imaging (MRI) can be used effectively to determine variation in cartilage morphometry - a crucial parameter for assessment of osteoarthritis. Segmentation of cartilage from surrounding tissues is a necessary preliminary step to the quantitation process. In this in-vivo study we implement the immersion based watershed algorithm to develop a novel and reliable cartilage segmentation technique. The protocol has been successfully applied to determine morphometric differences among normal, mild and severe osteoarthritic patient populations
Keywords :
biological tissues; biomedical MRI; image resolution; image segmentation; mathematical morphology; medical image processing; orthopaedics; articular cartilage; cartilage morphometry; high resolution magnetic resonance images; immersion based watershed algorithm; in-vivo MRI; knee; mild osteoarthritic patient population; morphometric differences; normal osteoarthritic patient population; osteoarthritis; protocol; severe osteoarthritic patient population; surrounding tissues; watershed segmentation; Coils; Degenerative diseases; Image resolution; Image segmentation; Knee; Magnetic resonance; Magnetic resonance imaging; Muscles; Osteoarthritis; Signal processing algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2000. Proceedings of the 22nd Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
ISSN :
1094-687X
Print_ISBN :
0-7803-6465-1
Type :
conf
DOI :
10.1109/IEMBS.2000.901563
Filename :
901563
Link To Document :
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