SEGMENTATION PROPAGATION FROM DEFORMABLE ATLASES FOR BRAIN MAPPING AND ANALYSIS
Marius George Linguraru, Tom K. Vercauteren, Mauricio Reyes Aguirre, Miguel Á. González Ballester, MA Gonzalez Ballester, Nicholas Ayache · BORIS (University Library Bern) · 2007
Magnetic resonance imaging (MRI) is commonly employed for the depiction of soft tissues, most notably the human brain. Computer-aided image analysis techniques lead to image enhancement and automatic detection of anatomical structures. However, the intensity information contained in images does not often offer enough contrast to robustly obtain a good detection of all internal brain structures, not least the deep gray matter nuclei. We propose digital atlases that deform to fit the image data to be analyzed. In this application, deformable atlases are employed for the detection and segmentation of brain nuclei, to allow analysis of brain structures. Our fully automatic technique is based on a combination of rigid, affine and non-linear registration, a priori information on key anatomical landmarks and propagation of the information of the atlas. The Internet Brain Segmentation Repository (IBSR) data provide manually segmented brain data. Using prior anatomical knowledge in local brain areas from a randomly chosen brain scan (atlas), a first estimation of the deformation fields is calculated by affine registration. The image alignment is refined through a non-linear transformation to correct the