Cart (Loading....) | Create Account
Close category search window
 

A statistical analysis of the effects of CT acquisition parameters on low-level features extracted from CT images of the lung

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Wantroba, J.S. ; Intell. Multimedia Process. Lab., DePaul Univ., Chicago, IL, USA ; Raicu, D.S. ; Furst, J.D.

We propose a solution for automatic classification of lung nodules in an environment with heterogeneous computed tomography (CT) acquisition parameters. Such a classification system needs to take into account the differences in CT acquisition parameters used when obtaining and processing each medical image. Using analysis of variance (ANOVA), our current research proposes to better understand the effects of CT acquisition parameters on predicting various semantic characteristics (such as spiculation, subtlety, and margin) used in the diagnosis interpretation process. All of the parameters were found to affect the low-level image features used in the classification models of these semantic characteristics. When this knowledge is used to normalize those parameters, the final semantic model will become unaffected by the CT acquisition parameters.

Published in:

Image Processing (ICIP), 2009 16th IEEE International Conference on

Date of Conference:

7-10 Nov. 2009

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.