Worcester Polytechnic Institute Electronic Theses and Dissertations Collection

Title page for ETD etd-020509-161314


Document Typethesis
Author NameQuartararo, John David
URNetd-020509-161314
TitleSemi-Automated Segmentation of 3D Medical Ultrasound Images
DegreeMS
DepartmentElectrical & Computer Engineering
Advisors
  • Peder C. Pedersen, Advisor
  • David Cyganski, Committee Member
  • Matthew Oliver Ward, Committee Member
  • Keywords
  • 3d ultrasound
  • ultrasound
  • image processing
  • image segmentation
  • 3d image segmentation
  • medical imaging
  • Date of Presentation/Defense2008-10-03
    Availability unrestricted

    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.

    Files
  • quartararo.pdf

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