An alignment procedure by maximizing image contrast across tissue boundaries rather than matching intensities between two images or by matching surface shapes. . BBR is more accurate than correlation ratio or normalized mutual information and is considerably more robust to even strong intensity inhomogeneities. BBR also excels at aligning partial brain images to whole brain images, a domain in which existing registration algorithms frequently fail. BBR is part of the FreeSurfer software package.
Martinos Center for Biomedical Imaging, Charlestown, MA, USA; MIT Computer Science and AI Lab/Division of Health Sciences and Technology, Cambridge, MA, USA
BBR funding source(s)
This work was supported by the National Center for Research Resources (P41-RR14075, R01 and RR16594-01A1), the NCRR BIRN Morphometric Project BIRN002, the Functional Imaging Biomedical Informatics Research Network (FBIRN) U24 RR021382), the National Institute for Biomedical Imaging and Bioengineering (R01 EB001550 and R01EB006758), the National Institute for Neurological Disorders and Stroke (R01 NS052585-01), the Mental Illness and Neuroscience Discovery (MIND) Institute, the National Alliance for Medical Image Computing (NAMIC) and the NIH Roadmap for Medical Research, Grant U54 EB005149. Additional support was provided by The Autism & Dyslexia Project funded by the Ellison Medical Foundation.