Statements (24)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
deep learning architecture
|
| gptkbp:activatedBy |
gptkb:PReLU
|
| gptkbp:application |
medical imaging
brain MRI segmentation prostate MRI segmentation |
| gptkbp:architecture |
encoder-decoder
|
| gptkbp:basedOn |
gptkb:convolutional_neural_network
|
| gptkbp:citation |
V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation
|
| gptkbp:hasSkipConnections |
true
|
| https://www.w3.org/2000/01/rdf-schema#label |
V-Net
|
| gptkbp:input |
3D volumetric data
|
| gptkbp:introducedIn |
2016
|
| gptkbp:lossFunction |
Dice loss
|
| gptkbp:output |
segmentation map
|
| gptkbp:proposedBy |
Fausto Milletari
Nassir Navab Seyed-Ahmad Ahmadi |
| gptkbp:publishedIn |
3D Vision (3DV), 2016 Fourth International Conference on
|
| gptkbp:relatedTo |
gptkb:U-Net
|
| gptkbp:usedFor |
medical image segmentation
|
| gptkbp:usesResidualConnections |
true
|
| gptkbp:bfsParent |
gptkb:UNet_architecture
gptkb:3D_U-Net |
| gptkbp:bfsLayer |
7
|