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Found 5 papers, 5 papers with code
CARZero: Cross-Attention Alignment for Radiology Zero-Shot Classification
The advancement of Zero-Shot Learning in the medical domain has been driven forward by using pre-trained models on large-scale image-text pairs, focusing on image-text alignment.
ECAMP: Entity-centered Context-aware Medical Vision Language Pre-training
Despite significant advancements in medical vision-language pre-training, existing methods have largely overlooked the inherent entity-specific context within radiology reports and the complex cross-modality contextual relationships between text and images.
Long-tailed multi-label classification with noisy label of thoracic diseases from chest X-ray
This work establishes a foundation for robust CAD methods, achieving a balance in identifying a spectrum of thoracic diseases in CXRs.
DLUNet: Semi-supervised Learning based Dual-Light UNet for Multi-organ Segmentation
In the training phase, it consists of two light UNets, which make full use of label and unlabeled data simultaneously by using consistent-based learning.
Semi-Supervised Hybrid Spine Network for Segmentation of Spine MR Images
In the first stage, we constructed a 2D semi-supervised DeepLabv3+ by using cross pseudo supervision to obtain intra-slice features and coarse segmentation.
