| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
A deep learning framework for unsupervised affine and deformable image registration
|
de Vos, Bob D.
|
|
2019
|
52 |
C |
p. 128-143
|
artikel
|
| 2 |
A graph-cut approach for pulmonary artery-vein segmentation in noncontrast CT images
|
Jimenez-Carretero, Daniel
|
|
2019
|
52 |
C |
p. 144-159
|
artikel
|
| 3 |
Automated diagnosis of breast ultrasonography images using deep neural networks
|
Qi, Xiaofeng
|
|
2019
|
52 |
C |
p. 185-198
|
artikel
|
| 4 |
Automated segmentation of knee bone and cartilage combining statistical shape knowledge and convolutional neural networks: Data from the Osteoarthritis Initiative
|
Ambellan, Felix
|
|
2019
|
52 |
C |
p. 109-118
|
artikel
|
| 5 |
Automatic graph-based method for localization of cochlear implant electrode arrays in clinical CT with sub-voxel accuracy
|
Zhao, Yiyuan
|
|
2019
|
52 |
C |
p. 1-12
|
artikel
|
| 6 |
CATARACTS: Challenge on automatic tool annotation for cataRACT surgery
|
Al Hajj, Hassan
|
|
2019
|
52 |
C |
p. 24-41
|
artikel
|
| 7 |
Editorial Board
|
|
|
2019
|
52 |
C |
p. ii
|
artikel
|
| 8 |
GAS: A genetic atlas selection strategy in multi-atlas segmentation framework
|
Antonelli, Michela
|
|
2019
|
52 |
C |
p. 97-108
|
artikel
|
| 9 |
Micro-Net: A unified model for segmentation of various objects in microscopy images
|
Raza, Shan E Ahmed
|
|
2019
|
52 |
C |
p. 160-173
|
artikel
|
| 10 |
MILD-Net: Minimal information loss dilated network for gland instance segmentation in colon histology images
|
Graham, Simon
|
|
2019
|
52 |
C |
p. 199-211
|
artikel
|
| 11 |
Motion artifact recognition and quantification in coronary CT angiography using convolutional neural networks
|
Lossau, T.
|
|
2019
|
52 |
C |
p. 68-79
|
artikel
|
| 12 |
Multimodal hyper-connectivity of functional networks using functionally-weighted LASSO for MCI classification
|
Li, Yang
|
|
2019
|
52 |
C |
p. 80-96
|
artikel
|
| 13 |
Quality-based UnwRap of SUbdivided Large Arrays (URSULA) for high-resolution MRI data
|
Lindemeyer, J.
|
|
2019
|
52 |
C |
p. 13-23
|
artikel
|
| 14 |
Reproducibility and intercorrelation of graph theoretical measures in structural brain connectivity networks
|
Roine, Timo
|
|
2019
|
52 |
C |
p. 56-67
|
artikel
|
| 15 |
Robust motion correction for cardiac T1 and ECV mapping using a T1 relaxation model approach
|
Tilborghs, Sofie
|
|
2019
|
52 |
C |
p. 212-227
|
artikel
|
| 16 |
Supervised learning for bone shape and cortical thickness estimation from CT images for finite element analysis
|
Chandran, Vimal
|
|
2019
|
52 |
C |
p. 42-55
|
artikel
|
| 17 |
The effect of motion correction interpolation on quantitative T1 mapping with MRI
|
Nachmani, Amitay
|
|
2019
|
52 |
C |
p. 119-127
|
artikel
|
| 18 |
Towards cross-modal organ translation and segmentation: A cycle- and shape-consistent generative adversarial network
|
Cai, Jinzheng
|
|
2019
|
52 |
C |
p. 174-184
|
artikel
|
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