title: Automated Segmentation of Cerebellum Using Brain Mask and Partial Volume Estimation Map.
abstract: While segmentation of the cerebellum is an indispensable step in many studies, its contrast is not clear because of the adjacent cerebrospinal fluid, meninges, and cerebra peduncle. Thus, various cerebellar segmentation methods, such as a deformable model or a template-based algorithm might exhibit incorrect segmentation of the venous sinuses and the cerebellar peduncle. In this study, we propose a fully automated procedure combining cerebellar tissue classification, a template-based approach, and morphological operations sequentially. The cerebellar region was defined approximately by removing the cerebral region from the brain mask. Then, the noncerebellar region was trimmed using a morphological operator and the brain-stem atlas was aligned to the individual brain to define the brain-stem area. The proposed method was validated with the well-known FreeSurfer and ITK-SNAP packages using the dice similarity index and recall and precision scores. As a result, the proposed method was significantly better than the other methods for the dice similarity index (0.93, FreeSurfer: 0.92, ITK-SNAP: 0.87) and precision (0.95, FreeSurfer: 0.90, ITK-SNAP: 0.93). Therefore, it could be said that the proposed method yielded a robust and accurate segmentation result. Moreover, additional postprocessing with the brain-stem atlas could improve its result.
authors.affiliation: Department of Biomedical Engineering, Hanyang University, Hangdang-dong, Sungdong-gu, Seoul 133-791, Republic of Korea.
authors.forename: Dong-Kyun
authors.initials: DK
authors.lastname: Lee
authors.affiliation: Department of Biomedical Engineering, Catholic University of Daegu, Daegu, Gyeongsan-si 712-702, Republic of Korea.
authors.forename: Uicheul
authors.initials: U
authors.lastname: Yoon
authors.affiliation: Department of Biomedical Engineering, Hanyang University, Hangdang-dong, Sungdong-gu, Seoul 133-791, Republic of Korea.
authors.forename: Kichang
authors.initials: K
authors.lastname: Kwak
authors.affiliation: Department of Biomedical Engineering, Hanyang University, Hangdang-dong, Sungdong-gu, Seoul 133-791, Republic of Korea.
authors.forename: Jong-Min
authors.initials: JM
authors.lastname: Lee
mesh_terms: D000328:Adult; D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology / Q000502:physiology; D001931:Brain Mapping; D002531:Cerebellum / Q000033:anatomy & histology* / Q000502:physiology; D019295:Computational Biology; D016208:Databases, Factual / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data; D008297:Male; D008953:Models, Anatomic; D008959:Models, Neurological; D055815:Young Adult