Automatic Human Knee Cartilage Segmentation From 3-D Magnetic Resonance Images

被引:89
作者
Dodin, Pierre [2 ]
Pelletier, Jean-Pierre [1 ]
Martel-Pelletier, Johanne [1 ]
Abram, Francois [2 ]
机构
[1] Univ Montreal Hosp Res Ctr CRCHUM, Notre Dame Hosp, Osteoarthritis Res Unit, Montreal, PQ H2L 4M1, Canada
[2] ArthroVis Inc, Montreal, PQ H2K 1B6, Canada
关键词
Cartilage volume; image resampling; magnetic resonance imaging (MRI); texture analysis; surface parameterization; three-dimensional segmentation; ARTICULAR-CARTILAGE; OSTEOARTHRITIC KNEES; MR; VOLUME; QUANTIFICATION; SURFACES; PRECISION; THICKNESS; JOINT; ECHO;
D O I
10.1109/TBME.2010.2058112
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
This study aimed at developing a new automatic segmentation algorithm for human knee cartilage volume quantification from MRI. Imaging was performed using a 3T scanner and a knee coil, and the exam consisted of a double echo steady state (DESS) sequence, which contrasts cartilage and soft tissues including the synovial fluid. The algorithm was developed on MRI 3-D images in which the bone-cartilage interface for the femur and tibia was segmented by an independent segmentation process, giving a parametric surface of the interface. First, the MR images are resampled in the neighborhood of the bone surface. Second, by using texture-analysis techniques optimized by filtering, the cartilage is discriminated as a bright and homogeneous tissue. This process of excluding soft tissues enables the detection of the external boundary of the cartilage. Third, a technology based on a Bayesian decision criterion enables the automatic separation of the cartilage and synovial fluid. Finally, the cartilage volume and changes in volume for an individual between visits was assessed using the developed technology. Validation included first, for nine knee osteoarthritis patients, a comparison of the cartilage volume and changes over time between the developed automatic system and a validated semi-automatic cartilage volume system, and second, for five knee osteoarthritis patients, a test-retest procedure. Data revealed excellent Pearson correlations and Dice similarity coefficients (DSC) for the global knee (r = 0.96, p < 0.0001, and median DSC = 0.84), for the femur (r = 0.95, p < 0.0001, and median DSC = 0.85), and the tibia (r = 0.83, p < 0.0001, and median DSC = 0.84). Very good similarity between the automatic and semi-automatic methods in regard to cartilage loss was also found for the global knee (r = 0.76 and p = 0.016) as well as for the femur (r = 0.79 and p = 0.011). The test-retest revealed an excellent measurement error of -0.3 +/- 1.6% for the global knee and 0.14 +/- 1.7% for the femur. In conclusion, the newly developed fully automatic method described herein provides accurate and precise quantification of knee cartilage volume and will be a valuable tool for clinical follow-up studies.
引用
收藏
页码:2699 / 2711
页数:13
相关论文
共 38 条
  • [11] Non-invasive determination of cartilage thickness throughout joint surfaces using magnetic resonance imaging
    Eckstein, F
    Adam, C
    Sittek, H
    Becker, C
    Milz, S
    Schulte, E
    Reiser, M
    Putz, R
    [J]. JOURNAL OF BIOMECHANICS, 1997, 30 (03) : 285 - 289
  • [12] Long-term and resegmentation precision of quantitative cartilage MR imaging (qMRI)
    Eckstein, F
    Heudorfer, L
    Faber, SC
    Burgkart, R
    Englmeier, KH
    Reiser, M
    [J]. OSTEOARTHRITIS AND CARTILAGE, 2002, 10 (12) : 922 - 928
  • [13] Interindividual variability and correlation among morphological parameters of knee joint cartilage plates: analysis with three-dimensional MR imaging
    Eckstein, F
    Winzheimer, M
    Hohe, J
    Englmeier, KH
    Reiser, M
    [J]. OSTEOARTHRITIS AND CARTILAGE, 2001, 9 (02) : 101 - 111
  • [14] Sample size estimation: How many individuals should be studied?
    Eng, J
    [J]. RADIOLOGY, 2003, 227 (02) : 309 - 313
  • [15] Erleben Kenny., 2005, J WSCG, P17
  • [16] FOLKESSON J, 2005, P MICCAI, P327
  • [17] Articular cartilage in the knee: Mapping of the physiologic parameters at MR imaging with a local gradient coil - Preliminary results
    Frank, LR
    Wong, EC
    Luh, WM
    Ahn, JM
    Resnick, D
    [J]. RADIOLOGY, 1999, 210 (01) : 241 - 246
  • [18] Fripp J., 2007, INT C MED IM COMP AS, V10, P186
  • [19] GODBOUT B, 1998, P VIS INT VI 98 VANC, P18
  • [20] Improved watershed transform for medical image segmentation using prior information
    Grau, V
    Mewes, AUJ
    Alcañiz, M
    Kikinis, R
    Warfield, SK
    [J]. IEEE TRANSACTIONS ON MEDICAL IMAGING, 2004, 23 (04) : 447 - 458