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cs.CV2024
Metadata-enhanced contrastive learning from retinal optical coherence tomography images
Robbie Holland, Oliver Leingang, Hrvoje BogunoviÄ +9
Deep learning has potential to automate screening, monitoring and grading of disease in medical images. Pretraining with contrastive learning enables models to extract robust and g…
cs.CV2024
Pay Attention to the Atlas: Atlas-Guided Test-Time Adaptation Method for Robust 3D Medical Image Segmentation
Jingjie Guo, Weitong Zhang, Matthew Sinclair +2
Convolutional neural networks (CNNs) often suffer from poor performance when tested on target data that differs from the training (source) data distribution, particularly in medica…