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.
Thesis
Graph-based segmentation of lymph nodes in CT data
University of Iowa
Master of Science (MS), University of Iowa
Autumn 2010
DOI: 10.17077/etd.9p2eb4bq
Free to read and download, Open Access
Abstract
Details
- Title: Subtitle
- Graph-based segmentation of lymph nodes in CT data
- Creators
- Yao Wang - University of Iowa
- Contributors
- Reinhard Beichel (Advisor)Milan Sonka (Committee Member)Andreas Wahle (Committee Member)
- Resource Type
- Thesis
- Degree Awarded
- Master of Science (MS), University of Iowa
- Degree in
- Electrical and Computer Engineering
- Date degree season
- Autumn 2010
- Publisher
- University of Iowa
- DOI
- 10.17077/etd.9p2eb4bq
- Number of pages
- vi, 75 pages
- Copyright
- Copyright 2010 Yao Wang
- Language
- English
- Description bibliographic
- Includes bibliographical references (pages 72-75).
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9983776766402771
Metrics
1340 File views/ downloads
342 Record Views