Name
Abstract | ||
|---|---|---|
Convolutional neural networks (CNNs) are being extensively used to analyze medical images given the remarkable performances achieved so far. Due to the non-transparent decision-making process, CNNs are thought to be black boxes, so hindering their applicability. We submit a novel visualization technique to shed light on CNNs decisions in a classification task. Brain magnetic resonance images are f... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/CBMS52027.2021.00102 | 2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS) |
Keywords | DocType | ISBN |
Visualization,Three-dimensional displays,Magnetic resonance imaging,Decision making,Data visualization,Magnetic resonance,Brain modeling | Conference | 978-1-6654-4121-6 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Edouard Villain | 1 | 0 | 0.34 |
| Giulia Maria Mattia | 2 | 0 | 0.34 |
| Federico Nemmi | 3 | 0 | 0.34 |
| Patrice Péran | 4 | 0 | 0.34 |
| Xavier Franceries | 5 | 0 | 0.34 |
| Marie Véronique le Lann | 6 | 0 | 0.34 |