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This paper proposes ReG-SAM, a SAM-based framework tailored to 2D vessel segmentation that leverages reference graph set for enhancing vascular representations and introduces two modality-aware representations derived from the reference masks.
This work proposes an image-domain dual-branch INR framework, termed I-FP-INR, which extends the original INR design by introducing an additional feature-processing branch, which aims to extract complementary feature embeddings to enhance the overall representation, thereby benefiting reconstruction.
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