Document Type
Thesis
Date of Degree
Fall 2010
Degree Name
MS (Master of Science)
Degree In
Electrical and Computer Engineering
First Advisor
Reinhard Beichel
Abstract
The quantitative assessment of lymph node size plays an important role in treatment of diseases like cancer. In current clinical practice, lymph nodes are analyzed manually based on very rough measures of long and/or short axis length, which is error prone. In this paper we present a graph-based lymph node segmentation method to enable the computer-aided three-dimensional (3D) assessment of lymph node size. Our method has been validated on 111 cases of enlarged lymph nodes imaged with X-ray computed tomography (CT). For unsigned surface positioning error, Hausdorff distance and Dice coefficient, the mean was around 0.5 mm, under 3.26 mm and above 0.77 respectively. On average, 5.3 seconds were required by our algorithm for the segmentation of a lymph node.
Keywords
lymph nodes, medical image segmentation, optimal surface
Pages
vi, 75
Bibliography
72-75
Copyright
Copyright 2010 Yao Wang