Lesion Detection
Lesion detection in medical imaging aims to automatically identify and locate abnormalities within various medical scans, improving diagnostic accuracy and efficiency. Current research heavily utilizes deep learning, employing architectures like U-Net, Faster R-CNN, Vision Transformers, and diffusion models, often incorporating attention mechanisms and multi-scale feature fusion to enhance performance, particularly for small or subtle lesions. These advancements hold significant promise for assisting radiologists in tasks such as cancer screening, disease monitoring, and treatment planning, ultimately improving patient care and outcomes.
Papers
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