Robust automatic corpus callosum analysis toolkit: mapping callosal development across heterogeneous multisite data

Alyssa H. Zhu; Arvin Saremi; Armand Amini; Ricardo Pires; Paul M. Thompson; Neda Jahanshad

doi:10.1117/12.2506661

21 December 2018 Robust automatic corpus callosum analysis toolkit: mapping callosal development across heterogeneous multisite data

Alyssa H. Zhu, Arvin Saremi, Armand Amini, Ricardo Pires, Paul M. Thompson, Neda Jahanshad

Author Affiliations +

Proceedings Volume 10975, 14th International Symposium on Medical Information Processing and Analysis; 109750M (2018) https://doi.org/10.1117/12.2506661
Event: 14th International Symposium on Medical Information Processing and Analysis, 2018, Mazatlán, Mexico

Abstract

The corpus callosum (CC) is the main neural pathway that communicates information between the brain’s hemispheres. Impairment of this pathway is evident in neurogenetic and developmental disorders, neurodegenerative diseases, and in many major psychiatric disorders, making the CC the focus of intense study. Prior studies often require manual input for segmentation, or have been single site, single modality, or fail to report on the reliability and generalizability of segmentations. We develop a Robust Automatic Corpus Callosum Analysis Toolkit (RACCAT) that segments the midsagittal CC from T1-weighted images, guided by diffusion MRI where available, to facilitate large-scale multimodal CC studies of its global, regional, and local (pointwise) structure. RACCAT was applied to data from 772 individuals aged 3-21 from the Pediatric Imaging, Neurocognition, and Genetics study, a developmental cohort imaged using multiple scanners and imaging protocols. CC area and fractional anisotropy were associated with age but also with site and scanner manufacturer; CC curvature also showed significant age associations but showed no detectable association with the scanning site, making it a robust developmental biomarker for multisite studies.

Citation Download Citation

Alyssa H. Zhu, Arvin Saremi, Armand Amini, Ricardo Pires, Paul M. Thompson, and Neda Jahanshad "Robust automatic corpus callosum analysis toolkit: mapping callosal development across heterogeneous multisite data", Proc. SPIE 10975, 14th International Symposium on Medical Information Processing and Analysis, 109750M (21 December 2018); https://doi.org/10.1117/12.2506661

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

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: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
8 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Image segmentation

Scanners

Brain

Reliability

Diffusion weighted imaging

Magnetic resonance imaging

Neuroimaging

Keywords/Phrases

Search In:

Publication Years