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C^2M-DoT: Cross-modal consistent multi-view medical report generation with domain transfer network
In addition, word-level optimization based on numbers ignores the semantics of reports and medical images, and the generated reports often cannot achieve good performance.
AMLP:Adaptive Masking Lesion Patches for Self-supervised Medical Image Segmentation
The proposed strategies effectively address limitations in applying masked modeling to medical images, tailored to capturing fine lesion details vital for segmentation tasks.
MvCo-DoT:Multi-View Contrastive Domain Transfer Network for Medical Report Generation
In clinical scenarios, multiple medical images with different views are usually generated at the same time, and they have high semantic consistency.
MPS-AMS: Masked Patches Selection and Adaptive Masking Strategy Based Self-Supervised Medical Image Segmentation
We leverage the masked patches selection strategy to choose masked patches with lesions to obtain more lesion representation information, and the adaptive masking strategy is utilized to help learn more mutual information and improve performance further.
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