A toolbox to visually explore cerebellar shape changes in cerebellar disease and dysfunction

S. Mazdak Abulnaga; Zhen Yang; Aaron Carass; Kalyani Kansal; Bruno M. Jedynak; Chiadi U. Onyike; Sarah H. Ying; Jerry L. Prince

doi:10.1117/12.2216584

24 March 2016 A toolbox to visually explore cerebellar shape changes in cerebellar disease and dysfunction

S. Mazdak Abulnaga, Zhen Yang, Aaron Carass, Kalyani Kansal, Bruno M. Jedynak, Chiadi U. Onyike, Sarah H. Ying, Jerry L. Prince

Author Affiliations +

Proceedings Volume 9785, Medical Imaging 2016: Computer-Aided Diagnosis; 97852P (2016) https://doi.org/10.1117/12.2216584
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

The cerebellum plays an important role in motor control and is also involved in cognitive processes. Cerebellar function is specialized by location, although the exact topographic functional relationship is not fully understood. The spinocerebellar ataxias are a group of neurodegenerative diseases that cause regional atrophy in the cerebellum, yielding distinct motor and cognitive problems. The ability to study the region-specific atrophy patterns can provide insight into the problem of relating cerebellar function to location. In an effort to study these structural change patterns, we developed a toolbox in MATLAB to provide researchers a unique way to visually explore the correlation between cerebellar lobule shape changes and function loss, with a rich set of visualization and analysis modules. In this paper, we outline the functions and highlight the utility of the toolbox. The toolbox takes as input landmark shape representations of subjects’ cerebellar substructures. A principal component analysis is used for dimension reduction. Following this, a linear discriminant analysis and a regression analysis can be performed to find the discriminant direction associated with a specific disease type, or the regression line of a specific functional measure can be generated. The characteristic structural change pattern of a disease type or of a functional score is visualized by sampling points on the discriminant or regression line. The sampled points are used to reconstruct synthetic cerebellar lobule shapes. We showed a few case studies highlighting the utility of the toolbox and we compare the analysis results with the literature.

Citation Download Citation

S. Mazdak Abulnaga, Zhen Yang, Aaron Carass, Kalyani Kansal, Bruno M. Jedynak, Chiadi U. Onyike, Sarah H. Ying, and Jerry L. Prince "A toolbox to visually explore cerebellar shape changes in cerebellar disease and dysfunction", Proc. SPIE 9785, Medical Imaging 2016: Computer-Aided Diagnosis, 97852P (24 March 2016); https://doi.org/10.1117/12.2216584

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
10 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Visualization

Cerebellum

Visual analytics

Principal component analysis

Shape analysis

Magnetic resonance imaging

Neodymium

Show All Keywords

Keywords/Phrases

Search In:

Publication Years