A volumetric vision-language model trained jointly on classification labels and segmentation masks from three CT datasets reaches 83% AUROC on CT-RATE and shows cross-dataset zero-shot behavior.
Joint segmentation and classification of skin lesions via a multi-task learning convolutional neural network
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Unified Supervision For Vision-Language Modeling in 3D Computed Tomography
A volumetric vision-language model trained jointly on classification labels and segmentation masks from three CT datasets reaches 83% AUROC on CT-RATE and shows cross-dataset zero-shot behavior.