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Found 4 papers, 1 papers with code
OphCLIP: Hierarchical Retrieval-Augmented Learning for Ophthalmic Surgical Video-Language Pretraining
Surgical practice involves complex visual interpretation, procedural skills, and advanced medical knowledge, making surgical vision-language pretraining (VLP) particularly challenging due to this complexity and the limited availability of annotated data.
VisionUnite: A Vision-Language Foundation Model for Ophthalmology Enhanced with Clinical Knowledge
The need for improved diagnostic methods in ophthalmology is acute, especially in the less developed regions with limited access to specialists and advanced equipment.
A Novel Hybrid Convolutional Neural Network for Accurate Organ Segmentation in 3D Head and Neck CT Images
An essential step of RT planning is the accurate segmentation of various organs-at-risks (OARs) in HaN CT images.
Group Shift Pointwise Convolution for Volumetric Medical Image Segmentation
Recent studies have witnessed the effectiveness of 3D convolutions on segmenting volumetric medical images.
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