Faculty Advisor or Committee Member

Peder C. Pedersen, Advisor

Faculty Advisor or Committee Member

Matthew Oliver Ward, Committee Member

Faculty Advisor or Committee Member

David Cyganski, Committee Member

Identifier

etd-020509-161314

Abstract

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.

Publisher

Worcester Polytechnic Institute

Degree Name

MS

Department

Electrical & Computer Engineering

Project Type

Thesis

Date Accepted

2009-02-05

Accessibility

Unrestricted

Subjects

3d ultrasound, ultrasound, image processing, image segmentation, 3d image segmentation, medical imaging, Three-dimensional imaging in medicine, Ultrasonic imaging

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