Name
Abstract | ||
|---|---|---|
•A system based on deep learning is shown to outperform a state-of-the art CAD system.•Adding complementary handcrafted features to the CNN is shown to increase performance.•The system based on deep learning is shown to perform at the level of a radiologist. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.media.2016.07.007 | Medical Image Analysis |
Keywords | Field | DocType |
Computer aided detection,Mammography,Deep learning,Machine learning,Breast cancer,Convolutional neural networks | Convolutional neural network,Computer science,Feature set,Artificial intelligence,Deep learning,Cad system,Deep neural networks,Object detection,Computer vision,Mammography,Pattern recognition,Computer aided detection,Machine learning | Journal |
Volume | ISSN | Citations |
35 | 1361-8415 | 71 |
PageRank | References | Authors |
2.40 | 34 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Thijs Kooi | 1 | 689 | 26.16 |
| Geert Litjens | 2 | 996 | 50.79 |
| Bram van Ginneken | 3 | 4979 | 307.23 |
| Albert Gubern-Mérida | 4 | 133 | 12.95 |
| C. I. Sánchez | 5 | 717 | 28.13 |
| ritse m mann | 6 | 104 | 9.39 |
| Ard den Heeten | 7 | 71 | 2.40 |
| Nico Karssemeijer | 8 | 992 | 122.49 |