Abstract #2851
Automatic Classification of Brain Tractography Data
Esha Datta 1 , Kesshi Jordan 1 , Eduardo Caverzasi 1 , and Roland Henry 1
1
University of California, San Francisco, San
Francisco, California, United States
Diffusion MRI tractography if often used in
pre-neurosurgical planning to map brain connections that
are considered critical to motor, visual, and language
function. Usually, this data is segmented manually
through a time consuming process requiring a trained
technician. This study explores the use of an
alternative automatic classification method, which uses
a training set to output a set of classified tracts from
a set of streamlines. This method correctly identifies
the rough volume of all tracts tested and for the left
IFOF, the tracts classified by the algorithm and the
tracts classified by humans were almost
indistinguishable (P-value = .9021).
This abstract and the presentation materials are available to members only;
a login is required.
Join Here
