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

A Statistical Modeling Approach for Tumor-Type Identification in Surgical Neuropathology Using Tissue Mass Spectrometry Imaging

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

4 Author(s)
Gholami, B. ; Dept. of Neurosurg., Harvard Med. Sch., Boston, MA, USA ; Norton, I. ; Eberlin, L.S. ; Agar, N.Y.R.

Current clinical practice involves classification of biopsied or resected tumor tissue based on a histopathological evaluation by a neuropathologist. In this paper, we propose a method for computer-aided histopathological evaluation using mass spectrometry imaging. Specifically, mass spectrometry imaging can be used to acquire the chemical composition of a tissue section and, hence, provides a framework to study the molecular composition of the sample while preserving the morphological features in the tissue. The proposed classification framework uses statistical modeling to identify the tumor type associated with a given sample. In addition, if the tumor type for a given tissue sample is unknown or there is a great degree of uncertainty associated with assigning the tumor type to one of the known tumor models, then the algorithm rejects the given sample without classification. Due to the modular nature of the proposed framework, new tumor models can be added without the need to retrain the algorithm on all existing tumor models.

Published in:

Biomedical and Health Informatics, IEEE Journal of  (Volume:17 ,  Issue: 3 )

Date of Publication:

May 2013

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.