Name
Title | ||
|---|---|---|
Computational methods for corpus callosum segmentation on MRI: A systematic literature review. |
Abstract | ||
|---|---|---|
•Because no reviews or surveys covering CC segmentation and parcellation so far, this work presents a systematic literature review about that theme.•From 802 publications reviewed, 36 studies were selected through the systematic literature review process.•This systematic review led to arrange main studies, focusing on CC segmentation, in four main groups: model-based, region-based, thresholding, and machine learning techniques. Besides, 32 metrics for method validation were summarized and reported.•The analyzed computational methods used to perform CC segmentation on magnetic resonance imaging have not yet overcome all presented challenges owing to metrics variability and lack of traceable materials. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.cmpb.2017.10.025 | Computer Methods and Programs in Biomedicine |
Keywords | Field | DocType |
Corpus callosum,Segmentation,Systematic literature review,Magnetic resonance imaging | Computer vision,Anatomy,Systematic review,Computer science,Segmentation,Natural language processing,Artificial intelligence,Corpus callosum,Magnetic resonance imaging | Journal |
Volume | ISSN | Citations |
154 | 0169-2607 | 1 |
PageRank | References | Authors |
0.35 | 30 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| G S Cover | 1 | 1 | 0.35 |
| W G Herrera | 2 | 1 | 0.35 |
| M P Bento | 3 | 1 | 0.35 |
| Simone Appenzeller | 4 | 14 | 4.99 |
| Leticia Rittner | 5 | 82 | 12.95 |