A text-guided CLIP-style model with a frozen BERT text encoder and cross-entropy alignment classifies focal liver lesions from multi-phase CT slices with about 79 percent average accuracy, outperforming CLIP and MedCLIP on a small in-house dataset.
-W.: Deep Neural Network - Based Classification of Focal Liver Lesions Using Phase-Shuffle Prediction Pre-training
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A Vision-Language Model for Focal Liver Lesion Classification
A text-guided CLIP-style model with a frozen BERT text encoder and cross-entropy alignment classifies focal liver lesions from multi-phase CT slices with about 79 percent average accuracy, outperforming CLIP and MedCLIP on a small in-house dataset.