medical imaging
Medical imaging involves the use of AI techniques to analyze images from medical sources, such as MRI, CT scans, and X-rays, to assist in diagnosis, monitoring diseases, and guiding treatment strategies.
- From Human Attention to Diagnosis: Semantic Patch-Level Integration of Vision-Language Models in Medical Imaging
- Gate to the Vessel: Residual Experts Restore What SAM Overlooks
- ImageNet-trained CNNs are not biased towards texture: Revisiting feature reliance through controlled suppression
- ImageNet-trained CNNs are not biased towards texture: Revisiting feature reliance through controlled suppression
- MedSG-Bench: A Benchmark for Medical Image Sequences Grounding
- OCTDiff: Bridged Diffusion Model for Portable OCT Super-Resolution and Enhancement
- Online Feedback Efficient Active Target Discovery in Partially Observable Environments
- Randomized-MLP Regularization Improves Domain Adaptation and Interpretability in DINOv2
- Toward a Vision-Language Foundation Model for Medical Data: Multimodal Dataset and Benchmarks for Vietnamese PET/CT Report Generation