1. Author :J. Carballido-Gamio J.S. Bauer Keh-YangLeeJ. Carballido-GamioJ.S. BauerKeh-YangLee S. Krause S. MajumdarS. KrauseS. Majumdar Source : 27th Annual International Conference of the IEEE-EMBS 2005; On page(s): 3043-3046 Speaker : Ren-Li Shen Advisor : Ku-Yaw Chang 12007/8/7

2. Outline Introduction Methodology Results Discussion Conclusion 22007/8/7

3. Introduction Articular cartilage Common manifestation of osteoarthritis (OA) Morphological degeneration Magnetic resonance imaging (MRI) Visualize and analyze Purpose Development new image processing techniques For quantitative analysis 32007/8/7

4. Introduction Image process consists MRI acquisition Cartilage segmentation Automatic Semi-automatic Interactive Interpolation Morphing technique Registration 3D shape-contexts Quantification Minimum 3D Euclidean distances 3D shape-contexts Visualization 42007/8/7

5. Outline Introduction Methodology Results Discussion Conclusion 52007/8/7

6. Methodology 17 porcine knees Sagittal 3D SPGR MR images （ Intra-subject ） Knee of 6 subjects （ resolution ： 0.234 mm x 0.234 mm, slice thickness ： 2mm,obtained at 1.5T ） Sagittal fast spin-echo(FSE) images （ Inter-subject ） Both knees of 6 different subjects （ resolution ： 0.3125 mm x 0.3125mm, slice thickness ： 1.5 mm,obtained at 1.5T ） 62007/8/7

7. Methodology 2007/8/77

8. Methodology -Cartilage segmentation Semi-automatic segmentation technique Based on edge detection and Bezier splines Control points Placed inside the cartilage Following its shape to create Bezier spline Smoothing techniques Anisotropic diffusion Median filtering Multiplication 2007/8/78

9. Methodology -Thickness and volume Compute 3D cartilage thickness Labeling bone-cartilage and articular Automatically For each point on the articular surface Can find point on the bone-cartilage interface Corresponding distance was assigned Thickness value 2007/8/79

10. Methodology -Image registration Bones to be registered Using 3D shape-contexts Robust contour matching Manual and automatic Using minimum Euclidean distances Avoid false matching 2007/8/710

11. Outline Introduction Methodology Results Discussion Conclusion 112007/8/7

12. Results Using Bland-Altman method Check for any deviation All methods Good agreement on all data samples 2007/8/712

13. Outline Introduction Methodology Results Discussion Conclusion 132007/8/7

14. Discussion Proper quantification of thickness and volume Important to OA of the knee In follow-up studies Compare common regions Have presented an validated Automatic registration technique 2007/8/714

15. Outline Introduction Methodology Results Discussion Conclusion 152007/8/7

16. Conclusion It’s important to assess the quantification Knee cartilage morphology Monitor the progression of joint diseases Have presented and validated Accurate image processing tools 2007/8/716

17. The end~ 2007/8/717