Document Type

Thesis

Date of Degree

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