Matthew Oliver Ward
Peder C. Pedersen
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.
Worcester Polytechnic Institute
Electrical & Computer Engineering
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Quartararo, John David, "Semi-Automated Segmentation of 3D Medical Ultrasound Images" (2009). Masters Theses (All Theses, All Years). 155.
3d ultrasound, ultrasound, image processing, image segmentation, 3d image segmentation, medical imaging, Three-dimensional imaging in medicine, Ultrasonic imaging