Mr. Ronald Pierson Profile

Ronald Pierson

at Univ of Iowa Hospitals and Clinics

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 27 March 2009 Paper

Maximize uniformity summation heuristic (MUSH): a highly accurate simple method for intracranial delineation

Ronald Pierson, Gregory Harris, Hans Johnson, Steve Dunn, Vincent Magnotta

Proceedings Volume 7259, 72593N (2009) https://doi.org/10.1117/12.812322

KEYWORDS: Brain, Neuroimaging, Tissues, Magnetic resonance imaging, Binary data, Functional imaging, Image registration, Skull, Natural surfaces, Scanners

Read Abstract +

A common procedure performed by many groups in the analysis of neuroimaging data is separating the brain from other tissues. This procedure is often utilized both by volumetric studies as well as functional imaging studies. Regardless of the intent, an accurate, robust method of identifying the brain or cranial vault is imperative. While this is a common requirement, there are relatively few tools to perform this task. Most of these tools require a T1 weighted image and are therefore not able to accurately define a region that includes surface CSF. In this paper, we have developed a novel brain extraction technique termed Maximize Uniformity by Summation Heuristic (MUSH) optimization. The algorithm was designed for extraction of the brain and surface CSF from a multi-modal magnetic resonance (MR) imaging study. The method forms a linear combination of multi-modal MR imaging data to make the signal intensity within the brain as uniform as possible. The resulting image is thresholded and simple morphological operators are utilized to generate the resulting representation of the brain. The resulting method was applied to a sample of 20 MR brain scans and compared to the results generated by 3dSkullStrip, 3dIntracranial, BET, and BET2. The average Jaccard metrics for the twenty subjects was 0.66 (BET), 0.61 (BET2), 0.88 (3dIntracranial), 0.91 (3dSkullStrip), and 0.94 (MUSH).

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

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:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years