1. A fully automated method for segmentation and thickness determination of hip joint cartilage from 3D MR data Authors: Yoshinobu Sato,et al. Source: Proceedings of the 15th International Congress and Exhibition, Berlin, Germany, June 27-30, 2001 Presented by: Ku-Yaw Chang

2. 22007/11/10Ku-Yaw Chang Outline IntroductionMethodResultsConclusion

3. 32007/11/10Ku-Yaw Chang Introduction Distribution of articular cartilage thickness important in the diagnosis of joint diseases important in the diagnosis of joint diseases Magnetic Resonance (MR) imaging The most suitable modality for cartilage imaging The most suitable modality for cartilage imaging

4. 42007/11/10Ku-Yaw Chang Introduction To develop a fully automated method Segmentation of hip joint cartilage Segmentation of hip joint cartilage Femoral head Acetabulum Determination of cartilage thickness Determination of cartilage thickness

5. 52007/11/10Ku-Yaw Chang Introduction MR images Leg traction Leg traction Clearly depict the articular space Assume that Both femoral and acetabular cartilage is distributed on a spherical surface whose center corresponds to the rotational center of the hip joint motion Both femoral and acetabular cartilage is distributed on a spherical surface whose center corresponds to the rotational center of the hip joint motion The proposed method is evaluated by using 13 sets of in vivo MR data of normal and diseased hip joints

6. 62007/11/10Ku-Yaw Chang Method Overview – four steps Automated determination of the center of a sphere that approximate the femoral head Automated determination of the center of a sphere that approximate the femoral head Hough transform Enhancement of cartilage regions and their inner edges Enhancement of cartilage regions and their inner edges First and second derivatives along radial directions originating from the sphere center

7. 72007/11/10Ku-Yaw Chang Method Overview – four steps (cont.) Automated segmentation of individual regions of femoral head and acetabular cartilage Automated segmentation of individual regions of femoral head and acetabular cartilage Radial derivate images using adaptive thresholding Automated subvoxel localization of cartilage boundaries for thickness determination Automated subvoxel localization of cartilage boundaries for thickness determination

8. 82007/11/10Ku-Yaw Chang Step One - Determination of Center Point Determination of center point of sphere approximating the femoral head Femoral head Femoral head A spherical shape with a radius of around 20 to 25 mm Center position is estimated from the 3D MR data Center position is estimated from the 3D MR data Hough transform

9. 92007/11/10Ku-Yaw Chang Step One - Determination of Center Point MR imaging protocol Cartilage is imaged much more brightly than bone Cartilage is imaged much more brightly than bone

10. 102007/11/10Ku-Yaw Chang Step One - Determination of Center Point Voxels around the boundaries of the femoral head and cartilage The direction of the gradient vector is aligned the direction from the femoral head center to the voxel position. The direction of the gradient vector is aligned the direction from the femoral head center to the voxel position. The magnitude of the gradient vector is large The magnitude of the gradient vector is large Hough transform with weighted voting Based on the gradient magnitude is performed Based on the gradient magnitude is performed

11. 112007/11/10Ku-Yaw Chang Step Two - Radial Directional Derivatives The directional first derivative Enhance cartilage-bone boundaries Enhance cartilage-bone boundaries The directional second derivative Enhance cartilage and articular space Enhance cartilage and articular space Combined with Gaussian blurring Combined with Gaussian blurring Different standard deviations (Multiscale integration) The above directional derivatives are used for Automated and accurate segmentation Automated and accurate segmentation Subvoxel localization Subvoxel localization

12. 122007/11/10Ku-Yaw Chang Step Three - Segmentation of Cartilage and Articular Space Regions Edge regions are extracted From the directional first derivative images From the directional first derivative images By By Adaptive thresholding Minimize overlooking true edge regions Minimize overlooking true edge regions Avoid any unwanted components being connected to the main component Avoid any unwanted components being connected to the main component Connectivity analysis

13. 132007/11/10Ku-Yaw Chang Step Three - Segmentation of Cartilage and Articular Space Regions The adaptive thresholding procedure (between the pelvic bone and acetabular cartilage): 1. Set the initial threshold value (which should be sufficiently low such that no overlooking occurs). 2. Threshold the radial directional first derivate images to obtain a binary image. 3. Extract the largest connective component from the binary image. 4. If the largest connective component satisfies the following condition, stop. Otherwise, increase the threshold value and go back to 1.

14. 142007/11/10Ku-Yaw Chang Step Three - Segmentation of Cartilage and Articular Space Regions Condition: Whether or not the extracted component is one- layer is checked Whether or not the extracted component is one- layer is checked Cartilage edge region should be a one-layer surface Rays along all radial directions originating from the femoral head center Pass only one or zero times through the cartilage region Pass only one or zero times through the cartilage region The number of rays passing through two or more layers should be sufficiently small The number of rays passing through two or more layers should be sufficiently small The edge region between the femur bone and femoral head cartilage is extracted in a similar way

15. 152007/11/10Ku-Yaw Chang Step Three - Segmentation of Cartilage and Articular Space Regions The approximated regions of cartilages are extracted from binarized versions of directional second derivative imags. The edge region are used as constrains to restrict the possible area for the cartilage and articular space regions The edge region are used as constrains to restrict the possible area for the cartilage and articular space regions

16. 162007/11/10Ku-Yaw Chang Step Four - Subvoxel Localization and Thickness Determination A subvoxel zero-crossing searching Along radial directions Along radial directions The thickness is estimated from the distance between Inner edge Inner edge Bone attached Outer edge Outer edge Articular space along radial directions.

17. 172007/11/10Ku-Yaw Chang Results