Name
Abstract | ||
|---|---|---|
Cortical surface-based morphometry is based on a semi-automated analysis of structural MRI images. In FreeSurfer, a widespread tool for surface-based analyses, a visual check of gray-white matter borders is followed by the manual placement of control points to drive the topological correction (editing) of segmented data. A novel algorithm combining radial sampling and machine learning is presented for the automated control point search (ACPS). |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.neuroimage.2018.04.035 | NeuroImage |
Keywords | Field | DocType |
Cortical surface-based,Morphometry,Data editing,Control points,Cortical thickness,Fractal dimensionality,Radial scanning,Machine learning | Surface reconstruction,Data set,Control point,Pattern recognition,Psychology,Cognitive psychology,Artificial intelligence,Data editing,Automated control | Journal |
Volume | ISSN | Citations |
176 | 1053-8119 | 0 |
PageRank | References | Authors |
0.34 | 16 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antonietta Canna | 1 | 0 | 0.34 |
| Andrea G. Russo | 2 | 0 | 0.34 |
| Sara Ponticorvo | 3 | 0 | 0.34 |
| Renzo Manara | 4 | 0 | 0.68 |
| Alessandro Pepino | 5 | 2 | 2.43 |
| Mario Sansone | 6 | 14 | 3.97 |
| Francesco Di Salle | 7 | 155 | 16.25 |
| Fabrizio Esposito | 8 | 421 | 36.61 |