1. MODULE II Semi-Automatic Segmentation
RSNA ITK-SNAP Course
Dec 1, 2015

2. Semi-Automatic Segmentation
User: quickly identifies structure of interest and sets parameters
Segmentation Algorithm

3. How does it work? Pre-segmentation Phase
Identify parts of image as foreground and background
Active Contour Phase
Place seeds inside the structure of interest
Grow the seeds to fill the structure of interest

4. Pre-segmentation Phase
Speed Image
Uncertain
Background
Foreground
Images
Region of Interest

5. Pre-segmentation Modes
Thresholding
sets thresholds
Classification
paints examples

6. Active Contour Evolution driven by Forces
Image Force: outward over foreground, inward over background
Smoothing Force: strongest in places of high curvature

7. Active Contour Evolution
places seeds

8. Live demo of semi-automatic segmentation

9. Please work on exercises 3 and 4