Watershed segmentation of high resolution magnetic resonance images of articular cartilage of the knee

S. Ghosh; O. Beuf; M. Ries; Nancy E Lane; L. S. Steinbach; T. M. Link; S. Majumdar

Watershed segmentation of high resolution magnetic resonance images of articular cartilage of the knee

S. Ghosh, O. Beuf, M. Ries, Nancy E Lane, L. S. Steinbach, T. M. Link, S. Majumdar

General Medicine, Geriatrics, and Bioethics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

15 Scopus citations

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.

Original language	English (US)
Title of host publication	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Editors	J.D. Enderle
Pages	3174-3176
Number of pages	3
Volume	4
State	Published - 2000
Event	22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Chicago, IL, United States Duration: Jul 23 2000 → Jul 28 2000

Other

Other	22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Country	United States
City	Chicago, IL
Period	7/23/00 → 7/28/00

Keywords

Articular cartilage
Image segmentation
Magnetic resonance imaging
Watershed algorithm

ASJC Scopus subject areas

Bioengineering

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Watershed segmentation of high resolution magnetic resonance images of articular cartilage of the knee. / Ghosh, S.; Beuf, O.; Ries, M.; Lane, Nancy E; Steinbach, L. S.; Link, T. M.; Majumdar, S.

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. ed. / J.D. Enderle. Vol. 4 2000. p. 3174-3176.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ghosh, S, Beuf, O, Ries, M, Lane, NE, Steinbach, LS, Link, TM & Majumdar, S 2000, Watershed segmentation of high resolution magnetic resonance images of articular cartilage of the knee. in JD Enderle (ed.), Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. vol. 4, pp. 3174-3176, 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Chicago, IL, United States, 7/23/00.

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keywords = "Articular cartilage, Image segmentation, Magnetic resonance imaging, Watershed algorithm",

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pages = "3174--3176",

editor = "J.D. Enderle",

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AU - Ghosh, S.

AU - Beuf, O.

AU - Ries, M.

AU - Lane, Nancy E

AU - Steinbach, L. S.

AU - Link, T. M.

AU - Majumdar, S.

PY - 2000

Y1 - 2000

N2 - 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.

AB - 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.

KW - Articular cartilage

KW - Image segmentation

KW - Magnetic resonance imaging

KW - Watershed algorithm

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M3 - Conference contribution

AN - SCOPUS:0034443078

VL - 4

SP - 3174

EP - 3176

BT - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

A2 - Enderle, J.D.

T2 - 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Y2 - 23 July 2000 through 28 July 2000

ER -

Watershed segmentation of high resolution magnetic resonance images of articular cartilage of the knee

Abstract

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Keywords

ASJC Scopus subject areas

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