Statistical bias in optimized VBM

Nicholas J. Tustison; Brian B. Avants; Philip A. Cook; James C. Gee; James R. Stone

doi:10.1117/12.2006377

29 March 2013 Statistical bias in optimized VBM

Nicholas J. Tustison, Brian B. Avants, Philip A. Cook, James C. Gee, James R. Stone

Author Affiliations +

Proceedings Volume 8672, Medical Imaging 2013: Biomedical Applications in Molecular, Structural, and Functional Imaging; 86720U (2013) https://doi.org/10.1117/12.2006377
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

The recent discovery of methodological flaws in experimental design and analysis in neuroscience research has raised concerns over the validity of certain techniques used in routine analyses and their corresponding findings. Such concerns have centered around selection bias whereby data is inadvertently manipulated such that the resulting analysis produces falsely increased statistical significance, i.e. type I errors. This has been illustrated recently in flv1RI studies, with excessive flexibility in data collection, and general experimental design issues. Current work from our group has shown how this problem extends to generic voxel-based analysis (and certain technique derivatives such as tract- based spatial statistics) using fractional anisotropy images derived from diffusion tensor imaging. In this work, we demonstrate how this circularity principle can potentially extend to the well-known optimized voxel-based morphometry technique for assessing cortical density differences whereby the principal cause of experimental corruption is due to normalization strategy. Specifically, the popular sum of-squared-differences (SSD) metric explicitly optimizes statistical findings potentially inflating type I errors. Additional experimentation demonstrates that this problem is not restricted to the SSD metric but extends to other commonly used metrics such as mutual information, neighborhood cross correlation, and Demons.

Citation Download Citation

Nicholas J. Tustison, Nicholas J. Tustison, Brian B. Avants, Brian B. Avants, Philip A. Cook, Philip A. Cook, James C. Gee, James C. Gee, James R. Stone, James R. Stone, } "Statistical bias in optimized VBM", Proc. SPIE 8672, Medical Imaging 2013: Biomedical Applications in Molecular, Structural, and Functional Imaging, 86720U (29 March 2013); doi: 10.1117/12.2006377; https://doi.org/10.1117/12.2006377

ACCESS THE FULL ARTICLE

PERSONAL SIGN IN
Full access may be available with your subscription

Email or Username Forgot your username?

Password Forgot your password?

Show

Remember Email/Username on this computer

Remember Password

No SPIE account? Create an account
or Institutional Sign In via Shibboleth

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $14.40

Non-members: $18.00 ADD TO CART

Show All Keywords

Keywords/Phrases

Search In:

Publication Years