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Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops; ISIC 2023, Care-AI 2 M. Emre Celebi,Md Sirajus Salekin,

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發(fā)表于 2025-3-30 09:56:18 | 只看該作者
Communication-Efficient Federated Skin Lesion Classification with?Generalizable Dataset Distillationnt federated skin lesion classification. Our framework includes the generalization dataset distillation (GDD) method, which explicitly models image features of the dataset into an uncertain Gaussian distribution and learns to produce synthetic images with features close to this distribution. The unc
52#
發(fā)表于 2025-3-30 14:34:34 | 只看該作者
AViT: Adapting Vision Transformers for Small Skin Lesion Segmentation Datasetslate the feature representation of a ViT without updating its pre-trained weights. In addition, we employ a shallow CNN as a prompt generator to create a prompt embedding from the input image, which grasps fine-grained information and CNN’s inductive biases to guide the segmentation task on small da
53#
發(fā)表于 2025-3-30 18:57:40 | 只看該作者
54#
發(fā)表于 2025-3-30 22:51:13 | 只看該作者
Generating Chinese Radiology Reports from?X-Ray Images: A Public Dataset and?an?X-ray-to-Reports Gendering linguistic disparities, we enhance the SOTA method with prompt training, graph-based augmentation, and sentence shuffling. Our CN-X2RG model shows significant improvements over baselines. The dataset and code are publicly available, fostering clinical-responsible research and development.
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