An automated method for segmenting magnetic resonance head images into brain and non-brain has been developed. It is very robust and accurate and has been tested on thousands of data sets from a wide variety of scanners and taken with a wide variety of MR sequences. The method, Brain Extraction Tool (BET), uses a deformable model that evolves to fit the brain's surface by the application of a set of locally adaptive model forces. The method is very fast and requires no preregistration or other pre-processing before being applied. We describe the new method and give examples of results and the results of extensive quantitative testing against "gold-standard" hand segmentations, and two other popular automated methods.

Original publication

DOI

10.1002/hbm.10062

Type

Journal article

Journal

Hum Brain Mapp

Publication Date

11/2002

Volume

17

Pages

143 - 155

Keywords

Algorithms, Animals, Brain, Humans, Magnetic Resonance Imaging