| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
A brain subcortical segmentation tool based on anatomy attentional fusion network for developing macaques
|
Zhong, Tao
|
|
|
116 |
C |
p.
|
artikel
|
| 2 |
Accurate segmentation of liver tumor from multi-modality non-contrast images using a dual-stream multi-level fusion framework
|
Xu, Chenchu
|
|
|
116 |
C |
p.
|
artikel
|
| 3 |
A comprehensive approach for evaluating lymphovascular invasion in invasive breast cancer: Leveraging multimodal MRI findings, radiomics, and deep learning analysis of intra- and peritumoral regions
|
Liu, Wen
|
|
|
116 |
C |
p.
|
artikel
|
| 4 |
A deep learning approach for virtual contrast enhancement in Contrast Enhanced Spectral Mammography
|
Rofena, Aurora
|
|
|
116 |
C |
p.
|
artikel
|
| 5 |
A 3D framework for segmentation of carotid artery vessel wall and identification of plaque compositions in multi-sequence MR images
|
Wang, Jian
|
|
|
116 |
C |
p.
|
artikel
|
| 6 |
An automatic radiomic-based approach for disease localization: A pilot study on COVID-19
|
Varriano, Giulia
|
|
|
116 |
C |
p.
|
artikel
|
| 7 |
2D/3D deformable registration for endoscopic camera images using self-supervised offline learning of intraoperative pneumothorax deformation
|
Oya, Tomoki
|
|
|
116 |
C |
p.
|
artikel
|
| 8 |
Deep learning ensembles for detecting brain metastases in longitudinal multi-modal MRI studies
|
Machura, Bartosz
|
|
|
116 |
C |
p.
|
artikel
|
| 9 |
Efficient multi-stage feedback attention for diverse lesion in cancer image segmentation
|
Arsa, Dewa Made Sri
|
|
|
116 |
C |
p.
|
artikel
|
| 10 |
Enhancing cancer prediction in challenging screen-detected incident lung nodules using time-series deep learning
|
Aslani, Shahab
|
|
|
116 |
C |
p.
|
artikel
|
| 11 |
Enhancing trabecular CT scans based on deep learning with multi-strategy fusion
|
Ge, Peixuan
|
|
|
116 |
C |
p.
|
artikel
|
| 12 |
Evidence modeling for reliability learning and interpretable decision-making under multi-modality medical image segmentation
|
Zhao, Jianfeng
|
|
|
116 |
C |
p.
|
artikel
|
| 13 |
FetalBrainAwareNet: Bridging GANs with anatomical insight for fetal ultrasound brain plane synthesis
|
Lasala, Angelo
|
|
|
116 |
C |
p.
|
artikel
|
| 14 |
Fragment distance-guided dual-stream learning for automatic pelvic fracture segmentation
|
Zeng, Bolun
|
|
|
116 |
C |
p.
|
artikel
|
| 15 |
Multi-objective Bayesian optimization with enhanced features for adaptively improved glioblastoma partitioning and survival prediction
|
Li, Yifan
|
|
|
116 |
C |
p.
|
artikel
|
| 16 |
PCa-RadHop: A transparent and lightweight feed-forward method for clinically significant prostate cancer segmentation
|
Magoulianitis, Vasileios
|
|
|
116 |
C |
p.
|
artikel
|
| 17 |
PFMNet: Prototype-based feature mapping network for few-shot domain adaptation in medical image segmentation
|
Wang, Runze
|
|
|
116 |
C |
p.
|
artikel
|
| 18 |
Precision dose prediction for breast cancer patients undergoing IMRT: The Swin-UMamba-Channel Model
|
Xie, Hui
|
|
|
116 |
C |
p.
|
artikel
|
| 19 |
Progress and trends in neurological disorders research based on deep learning
|
Iqbal, Muhammad Shahid
|
|
|
116 |
C |
p.
|
artikel
|
| 20 |
Radiomic-based prediction of lesion-specific systemic treatment response in metastatic disease
|
Geady, Caryn
|
|
|
116 |
C |
p.
|
artikel
|
| 21 |
ScribSD+: Scribble-supervised medical image segmentation based on simultaneous multi-scale knowledge distillation and class-wise contrastive regularization
|
Qu, Yijie
|
|
|
116 |
C |
p.
|
artikel
|
| 22 |
TLF: Triple learning framework for intracranial aneurysms segmentation from unreliable labeled CTA scans
|
Chai, Lei
|
|
|
116 |
C |
p.
|
artikel
|
| 23 |
Uncertainty estimation using a 3D probabilistic U-Net for segmentation with small radiotherapy clinical trial datasets
|
Chlap, Phillip
|
|
|
116 |
C |
p.
|
artikel
|
| 24 |
Unsupervised domain adaptation based on feature and edge alignment for femur X-ray image segmentation
|
Jiang, Xiaoming
|
|
|
116 |
C |
p.
|
artikel
|
| 25 |
Weakly supervised detection of pheochromocytomas and paragangliomas in CT using noisy data
|
Oluigbo, David
|
|
|
116 |
C |
p.
|
artikel
|
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