Bone labelling on micro-magnetic resonance images.
The study of trabecular bone is receiving increasing interest within the medical community working in the field of skeletal diseases, such as osteoporosis. Quantification of trabecular bone structure usually requires as a starting point a correct segmentation of the trabecular network. We have developed a probabilistic relaxation labelling technique, which uses local features of the trabecular bone images to improve segmentation. Tests on synthetic images show that bone labelling performs a more accurate segmentation than conventional techniques such as thresholding, especially by preserving the connectivity of the trabecular network. Tests on acquired data show that porosity values obtained after segmentation are in good agreement with experimental values obtained by weighing the bone samples.
Antoniadis
T
T
Unité de Recherche en Résonance Magnétique Médicale, U2R2M, CNRS URA 2212, Université Paris-Sud, Orsay, France.
Scarpelli
J P
JP
Ruaud
J P
JP
Gonord
P
P
Guillot
G
G
D000465:Algorithms; D001842:Bone and Bones / Q000033:anatomy & histology*; D016009:Chi-Square Distribution; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008954:Models, Biological; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity