Name
Title | ||
|---|---|---|
Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks. |
Abstract | ||
|---|---|---|
•Different types of uncertainties for deep-learning based medical image segmentation were analysed.•We propose a general aleatoric uncertainty estimation method based on test-time augmentation.•A theoretical formulation of test-time augmentation was proposed.•The proposed method was validated with 2D fetal brain segmentation and 3D brain tumor segmentation tasks. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.neucom.2019.01.103 | Neurocomputing |
Keywords | DocType | Volume |
Uncertainty estimation,Convolutional neural networks,Medical image segmentation,Data augmentation | Journal | 338 |
ISSN | Citations | PageRank |
0925-2312 | 13 | 0.69 |
References | Authors | |
31 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guotai Wang | 1 | 87 | 7.68 |
| Wenqi Li | 2 | 309 | 20.82 |
| Michael Aertsen | 3 | 81 | 6.21 |
| Jan Deprest | 4 | 123 | 20.45 |
| Sébastien Ourselin | 5 | 2499 | 237.61 |
| Tom Vercauteren | 6 | 1956 | 108.68 |