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Automated cerebellar lobule segmentation with application to cerebellar structural analysis in cerebellar disease
| Content Provider | Scilit |
|---|---|
| Author | Yang, Zhen Ye, Chuyang Bogovic, John A. Carass, Aaron Jedynak, Bruno M. Ying, Sarah H. Prince, Jerry L. |
| Copyright Year | 2016 |
| Description | Journal: NeuroImage The cerebellum plays an important role in both motor control and cognitive function. Cerebellar function is topographically organized and diseases that affect specific parts of the cerebellum are associated with specific patterns of symptoms. Accordingly, delineation and quantification of cerebellar sub-regions from magnetic resonance images are important in the study of cerebellar atrophy and associated functional losses. This paper describes an automated cerebellar lobule segmentation method based on a graph cut segmentation framework. Results from multi-atlas labeling and tissue classification contribute to the region terms in the graph cut energy function and boundary classification contributes to the boundary term in the energy function. A cerebellar parcellation is achieved by minimizing the energy function using the α-expansion technique. The proposed method was evaluated using a leave-one-out cross-validation on 15 subjects including both healthy controls and patients with cerebellar diseases. Based on reported Dice coefficients, the proposed method outperforms two state-of-the-art methods. The proposed method was then applied to 77 subjects to study the region-specific cerebellar structural differences in three spinocerebellar ataxia (SCA) genetic subtypes. Quantitative analysis of the lobule volumes shows distinct patterns of volume changes associated with different SCA subtypes consistent with known patterns of atrophy in these genetic subtypes. |
| Related Links | http://europepmc.org/articles/pmc4755820?pdf=render https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4755820/pdf |
| Ending Page | 444 |
| Page Count | 10 |
| Starting Page | 435 |
| ISSN | 10538119 |
| DOI | 10.1016/j.neuroimage.2015.09.032 |
| Journal | NeuroImage |
| Volume Number | 127 |
| Language | English |
| Publisher | Elsevier BV |
| Publisher Date | 2016-02-01 |
| Access Restriction | Open |
| Subject Keyword | Journal: NeuroImage Cerebellar Lobule Segmentation Magnetic Resonance Imaging Multi-atlas Labeling Random Forest Classifier Spinocerebellar Ataxia |
| Content Type | Text |
| Resource Type | Article |
| Subject | Neurology Cognitive Neuroscience |
