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Found 3 papers, 1 papers with code
Dual-scale Enhanced and Cross-generative Consistency Learning for Semi-supervised Polyp Segmentation
To address scale variation, we present a scale-enhanced consistency constraint, which ensures consistency in the segmentation maps generated from the same input image at different scales.
SegRap2023: A Benchmark of Organs-at-Risk and Gross Tumor Volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma
The precise delineation of Gross Tumor Volumes (GTVs) and Organs-At-Risk (OARs) is crucial in radiation treatment, directly impacting patient prognosis.
Segment Anything Model-guided Collaborative Learning Network for Scribble-supervised Polyp Segmentation
Specifically, we first propose a Cross-level Enhancement and Aggregation Network (CEA-Net) for weakly-supervised polyp segmentation.
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