A level set-based segmentation procedure has been implemented to identify target object boundaries from 3D medical ultrasound images. Several test images (simulated, scanned phantoms, clinical) were subjected to various preprocessing methods and segmented. Two metrics of segmentation accuracy were used to compare the segmentation results to ground truth models and determine which preprocessing methods resulted in the best segmentations. It was found that by using an anisotropic diffusion filtering method to reduce speckle type noise with a 3D active contour segmentation routine using the level set method resulted in semi-automated segmentation on par with medical doctors hand-outlining the same images.
| Identifer | oai:union.ndltd.org:wpi.edu/oai:digitalcommons.wpi.edu:etd-theses-1154 |
| Date | 05 February 2009 |
| Creators | Quartararo, John David |
| Contributors | Matthew O. Ward, Committee Member, Peder C. Pedersen, Advisor, David Cyganski, Committee Member |
| Publisher | Digital WPI |
| Source Sets | Worcester Polytechnic Institute |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Masters Theses (All Theses, All Years) |
Page generated in 0.0016 seconds