Name
Title | ||
|---|---|---|
Local spatio-temporal encoding of raw perfusion MRI for the prediction of final lesion in stroke. |
Abstract | ||
|---|---|---|
•Raw perfusion MRI images are used to predict final lesion in acute ischemic stroke.•This is obtained with a local spatio-temporal encoding.•Prediction results are shown similar to the one obtained with state of the art postprocessing. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.media.2018.08.008 | Medical Image Analysis |
Keywords | Field | DocType |
Local binary pattern,Support vector machine,Dynamic susceptibility contrast perfusion MRI,Stroke | Voxel,Computer vision,Lesion,Pattern recognition,Local binary patterns,Support vector machine,Deconvolution,Stroke,Artificial intelligence,Mathematics,Perfusion,Encoding (memory) | Journal |
Volume | ISSN | Citations |
50 | 1361-8415 | 0 |
PageRank | References | Authors |
0.34 | 15 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mathilde Giacalone | 1 | 1 | 1.37 |
| Pejman Rasti | 2 | 45 | 7.13 |
| Noelie Debs | 3 | 0 | 1.35 |
| Carole Frindel | 4 | 35 | 9.07 |
| Taehee Cho | 5 | 23 | 7.06 |
| E. Grenier | 6 | 4 | 2.69 |
| David Rousseau | 7 | 70 | 14.44 |