A joint project of the Graduate School, Peabody College, and the Jean & Alexander Heard Library

Title page for ETD etd-03312010-174848


Type of Document Master's Thesis
Author Glisson, Courtenay Locke
URN etd-03312010-174848
Title Comparison and assessment of semiautomatic image segmentation in computed tomography scans of the kidney.
Degree Master of Science
Department Biomedical Engineering
Advisory Committee
Advisor Name Title
Dr. Michael I. Miga Committee Member
Dr. Robert L. Galloway Committee Member
Keywords
  • image guidance
  • image processing
  • segmentation
  • kidney
Date of Defense 2010-03-31
Availability unrestricted
Abstract
Segmentation, or delineation of the boundaries of a region of interest, is an integral part of implementing intraoperative image guidance for kidney tumor resection. Results are affected by the kidney's physiology and pathology as seen in 3-D image data sets, as well as by the methods guiding contour growth. This work explores the variables involved in using level set methods to segment the kidney from computed tomography (CT) images. Multiple level set classes found in the Insight Toolkit were utilized to build a single, semi-automatic segmentation algorithm. This algorithm takes seed points and the image's contrast state as user input and functions independently thereafter. Comparison of the semi-automatic algorithm to an expert's hand-delineation of boundaries, hereafter "handsegmentation," showed that the algorithm performed well both for the images used in its creation and for new image sets. The algorithm also showed lower variability between raters than did handsegmentation. The automatic method's ability to function in a realistic image guidance situation was also evaluated. For three open kidney surgical cases, intraoperative laser range scans were registered to surfaces generated by both handsegmentation and the semi-automatic algorithm. Mean closest point distances between these registered surfaces as well as visual inspection of the distribution of closest point distances showed that the semi-automatic method provided a surface for registration which was comparable to handsegmentation. The inverse of each resultant transformation from these registrations was applied to CT image points, and variability introduced by the different transformations was found to be low, supporting the comparability of the autosegmentation to handsegmentation.
Files
  Filename       Size       Approximate Download Time (Hours:Minutes:Seconds) 
 
 28.8 Modem   56K Modem   ISDN (64 Kb)   ISDN (128 Kb)   Higher-speed Access 
  MastersFinal_PrelimBodyRefs.pdf 734.69 Kb 00:03:24 00:01:44 00:01:31 00:00:45 00:00:03

Browse All Available ETDs by ( Author | Department )

If you have more questions or technical problems, please Contact LITS.