Semi-automatic segmentation of knee osteoarthritic cartilage in magnetic resonance images
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Standard
Semi-automatic segmentation of knee osteoarthritic cartilage in magnetic resonance images. / Marstal, Kasper; Gudbergsen, Henrik; Boesen, Mikael; Kubassova, Olga; Bouert, Rasmus; Bliddal, Henning.
Proceedings ELMAR-2011 - 53rd International Symposium ELMAR-2011. 2011. s. 385-388 6044251 (Proceedings Elmar - International Symposium Electronics in Marine).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Harvard
APA
Vancouver
Author
Bibtex
}
RIS
TY - GEN
T1 - Semi-automatic segmentation of knee osteoarthritic cartilage in magnetic resonance images
AU - Marstal, Kasper
AU - Gudbergsen, Henrik
AU - Boesen, Mikael
AU - Kubassova, Olga
AU - Bouert, Rasmus
AU - Bliddal, Henning
PY - 2011
Y1 - 2011
N2 - Knee osteoarthritis is one of the major socio-economic burdens of today. Magnetic resonance imaging facilitates analysis of disease progression by visualization of structural and biochemical changes in cartilage tissue. Segmentation of cartilages from magnetic resonance images is therefore important in clinical investigations. Today, segmentations are obtained using time-consuming manual or semi-automatic algorithms that are subject to some degree of inter- and intra-observer variabilities. Automated methods are rarely used in clinical practice but have obvious advantages over manual methods and the potential to improve clinical workflow. This paper presents an algorithm for segmentation of knee articular cartilage in magnetic resonance images. The method is semi-automatic and requires a minimal amount of manual intervention. The proposed method is tested on scans from 50 subjects with all degrees of knee osteoarthritis as defined by the Kellgren-Lawrence grading scale and achieves an average sensitivity, specificity and dice similarity coefficient of 0.853±0.093, 0.999±0.001, 0.800±0.106 and 0.831±0.095, 0.999±0.001, 0.777±0.054 on tibial and femoral cartilages respectively. The method allows for segmentation of pathological cartilage in clinical investigations.
AB - Knee osteoarthritis is one of the major socio-economic burdens of today. Magnetic resonance imaging facilitates analysis of disease progression by visualization of structural and biochemical changes in cartilage tissue. Segmentation of cartilages from magnetic resonance images is therefore important in clinical investigations. Today, segmentations are obtained using time-consuming manual or semi-automatic algorithms that are subject to some degree of inter- and intra-observer variabilities. Automated methods are rarely used in clinical practice but have obvious advantages over manual methods and the potential to improve clinical workflow. This paper presents an algorithm for segmentation of knee articular cartilage in magnetic resonance images. The method is semi-automatic and requires a minimal amount of manual intervention. The proposed method is tested on scans from 50 subjects with all degrees of knee osteoarthritis as defined by the Kellgren-Lawrence grading scale and achieves an average sensitivity, specificity and dice similarity coefficient of 0.853±0.093, 0.999±0.001, 0.800±0.106 and 0.831±0.095, 0.999±0.001, 0.777±0.054 on tibial and femoral cartilages respectively. The method allows for segmentation of pathological cartilage in clinical investigations.
KW - cartilage
KW - knee osteoarthritis
KW - magnetic resonance imaging
KW - segmentation
UR - http://www.scopus.com/inward/record.url?scp=80055093857&partnerID=8YFLogxK
M3 - Article in proceedings
AN - SCOPUS:80055093857
SN - 9789537044121
T3 - Proceedings Elmar - International Symposium Electronics in Marine
SP - 385
EP - 388
BT - Proceedings ELMAR-2011 - 53rd International Symposium ELMAR-2011
T2 - 53rd International Symposium ELMAR-2011
Y2 - 14 September 2011 through 16 September 2011
ER -
ID: 319537939