title: Bayesian segmentation of brainstem structures in MRI.
abstract: In this paper we present a method to segment four brainstem structures (midbrain, pons, medulla oblongata and superior cerebellar peduncle) from 3D brain MRI scans. The segmentation method relies on a probabilistic atlas of the brainstem and its neighboring brain structures. To build the atlas, we combined a dataset of 39 scans with already existing manual delineations of the whole brainstem and a dataset of 10 scans in which the brainstem structures were manually labeled with a protocol that was specifically designed for this study. The resulting atlas can be used in a Bayesian framework to segment the brainstem structures in novel scans. Thanks to the generative nature of the scheme, the segmentation method is robust to changes in MRI contrast or acquisition hardware. Using cross validation, we show that the algorithm can segment the structures in previously unseen T1 and FLAIR scans with great accuracy (mean error under 1mm) and robustness (no failures in 383 scans including 168 AD cases). We also indirectly evaluate the algorithm with a experiment in which we study the atrophy of the brainstem in aging. The results show that, when used simultaneously, the volumes of the midbrain, pons and medulla are significantly more predictive of age than the volume of the entire brainstem, estimated as their sum. The results also demonstrate that the method can detect atrophy patterns in the brainstem structures that have been previously described in the literature. Finally, we demonstrate that the proposed algorithm is able to detect differential effects of AD on the brainstem structures. The method will be implemented as part of the popular neuroimaging package FreeSurfer.
authors.affiliation: Basque Center on Cognition, Brain and Language (BCBL), Spain. Electronic address: e.iglesias@bcbl.eu.
authors.forename: Juan Eugenio
authors.initials: JE
authors.lastname: Iglesias
authors.affiliation: Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU), Denmark; Departments of Information and Computer Science and of Biomedical Engineering and Computational Science, Aalto University, Finland.
authors.forename: Koen
authors.initials: K
authors.lastname: Van Leemput
authors.affiliation: Memory and Aging Center, University of California, San Francisco, CA, USA.
authors.forename: Priyanka
authors.initials: P
authors.lastname: Bhatt
authors.affiliation: Memory and Aging Center, University of California, San Francisco, CA, USA.
authors.forename: Christen
authors.initials: C
authors.lastname: Casillas
authors.affiliation: Memory and Aging Center, University of California, San Francisco, CA, USA.
authors.forename: Shubir
authors.initials: S
authors.lastname: Dutt
authors.affiliation: Center for Imaging of Neurodegenerative Dieases (CIND), Department of Radiology, University of California, San Francisco, CA, USA.
authors.forename: Norbert
authors.initials: N
authors.lastname: Schuff
authors.affiliation: Center for Imaging of Neurodegenerative Dieases (CIND), Department of Radiology, University of California, San Francisco, CA, USA.
authors.forename: Diana
authors.initials: D
authors.lastname: Truran-Sacrey
authors.affiliation: Memory and Aging Center, University of California, San Francisco, CA, USA.
authors.forename: Adam
authors.initials: A
authors.lastname: Boxer
authors.affiliation: Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology (MIT), Cambridge, MA, USA.
authors.forename: Bruce
authors.initials: B
authors.lastname: Fischl
mesh_terms: D000368:Aged; D000375:Aging / Q000502:physiology; D000465:Algorithms; D001271:Atlases as Topic; D001284:Atrophy; D001499:Bayes Theorem; D001933:Brain Stem / Q000033:anatomy & histology* / Q000254:growth & development / Q000502:physiology*; D066264:Datasets as Topic; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000706:statistics & numerical data*; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data*; D008297:Male; D008636:Mesencephalon / Q000033:anatomy & histology / Q000502:physiology; D008875:Middle Aged; D015233:Models, Statistical; D011149:Pons / Q000033:anatomy & histology / Q000502:physiology; D015203:Reproducibility of Results
keywords: Bayesian segmentation; Brainstem; Probabilistic atlas