Dense Rotation Invariant Brain Pyramids for Automated Human Brain Parcellation
Henrik Skibbe, Marco Reisert
Emerging Technologies for Medical Diagnosis and Therapy at INFORMATIK 2011 - Informatik schafft Communities
Berlin 2011
Berlin 2011
Abstract: The automatic parcellation of the human brain based on MR imaging is in
several areas of high interest. In particular, identifying corresponding
brain areas between different subjects is an indispensable prerequisite for
any group analysis. But also, simple segmentations into different tissue
types is an important preprocessing step. We present a generic framework
for describing and automatically parcellating high angular resolution
diffusion-weighted magnetic-resonance images (HARDI) of the human brain.
Based on an initial training step our approach is capable to segment the
images into coarse parcellations or detailed fine grain regions of
interest. In contrast to existing model-free methods we are not
only using the raw measurements at each position, but we are also including
neighboring measurements in a rotation invariant way.