1. X-ray Image Segmentation using Active Shape Models
Mayuresh Kulkarni
(KLKMAY001)
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

2. Presentation Overview
Introduction
Problem Description
Basic Segmentation Techniques
Active Shape Models (ASMs)
Performance Evaluation of ASMs
Conclusions
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

3. Mayuresh Kulkarni (BSc. Elec. Eng. UCT)
Introduction
Medical Imaging
Using Digital Imaging for applications in medicine
MRI scans, CT scans, digital X-rays etc.
In this thesis
Digital X-rays of the tibia
Image Segmentation
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

4. Mayuresh Kulkarni (BSc. Elec. Eng. UCT)
The Problem
The Big Picture
Detecting bone fractures automatically
X-ray Image segmentation
Feature Extraction
Pattern Recognition
The first step
X-ray image segmentation
Extracting the bone from the image
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

5. Basic Segmentation Techniques
Image Segmentation methods
Edge detection: Sobel, Prewitt, Roberts, Canny
Texture Analysis: Range and Std filtering
Limitations of basic techniques
Detect all edges
Detects the skin and the bone edge
Difficult to separate the bone from the X-ray
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

6. Filtering and Thresholding
Assumes that X-rays are ideal
The brightness is uniform
Bone boundary is brighter than the skin boundary
2 Levels of thresholding
Multiplying mask with original image
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

7. Filtering and Thresholding
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

8. Mayuresh Kulkarni (BSc. Elec. Eng. UCT)
Active Shape Models
Training images are landmarked
Learning the shape from training images
Creating profile models at landmark points
Recording the shape
Searching the shape in the test image
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

9. Mayuresh Kulkarni (BSc. Elec. Eng. UCT)
ASM: Sub-models
Profile Model
Analyzes the landmark points
Stores the image behaviour around landmarks
Builds a profile model for each landmark
Shape Model
Defines the permissible shapes and landmarks
Introduces a constraint on the search shape
Calculates the mean shape
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

10. Mayuresh Kulkarni (BSc. Elec. Eng. UCT)
Training Images
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

11. Mayuresh Kulkarni (BSc. Elec. Eng. UCT)
The Mean Shapes
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

12. Mayuresh Kulkarni (BSc. Elec. Eng. UCT)
Creating profile
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

13. Mayuresh Kulkarni (BSc. Elec. Eng. UCT)
Searching the shape
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

14. Mayuresh Kulkarni (BSc. Elec. Eng. UCT)
Defining the Error
Hand annotating the X-ray images
Distance transform
Comparing the ASM output to hand annotated images
Visual Check
Does the ASM track the bone?
Is it effective?
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

15. Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

16. Performance Evaluation
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

17. Performance Evaluation
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

18. Performance Evaluation
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

19. Performance Evaluation
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

20. Mayuresh Kulkarni (BSc. Elec. Eng. UCT)
Conclusions
Basic segmentation techniques
Work for certain images
Separate the bone
But are susceptible to noise
Active Shape Models
Extract the bone effectively
Perform well with different bone orientations
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

21. Mayuresh Kulkarni (BSc. Elec. Eng. UCT)
THANK YOU
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

22. Mayuresh Kulkarni (BSc. Elec. Eng. UCT)
References
M. Donnelley. Computer aided Long-bone Segmentation and Fracture Detection. PhD thesis, Flinders University of South Australia, January 2008.
C. Ying. Model-Based Approach for Extracting Femur Contours in X-ray Images. Master’s thesis, National University of Singapore, 2005.
T. F. Cootes and C. J. Taylor. Technical Report: Statistical Models of Appearance for Computer Vision. Technical report, The University of Manchester School of Medicine, 2004.
T. F. Cootes, C. J. Taylor, D. Cooper, and J. Graham. A Trainable Method of Parametric Shape Description. 2nd British Machine Vision Conference, pages 54–61, 1991.
S. E. Lim, Y. Xing, Y. Chen, W. K. Leow, T. S. Howe, and M. A. Png. Detection of Femur and Radius Fractures in X-Ray Images. 2nd International Conference on Advances in Medical Signal and Information, pages 249–256, 2004.
V. L. F. Lum, W. K. Leow, Y. Chen, T. S. Howe, and M. A. Png. Combining classifiers for bone fracture detection in X-ray Images.
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)

23. Mayuresh Kulkarni (BSc. Elec. Eng. UCT)
References
8. T. P. Tian, Y. Chen, W. K. Leow, W. Hsu, T. S. Howe, and M. A. Png. Computing neck- shaft angle of femur for x-ray fracture detection. International Conference on Computer Analysis of Images and Patterns, 2003.
T. T. Peng. Detection of Femur Fractures in X-ray images. PhD thesis, National University of Singapore, 2002.
Mayuresh Kulkarni (BSc. Elec. Eng. UCT)