6 papers · 1 filter
MARIO: A Mixed Annotation Framework For Polyp Segmentation
Haoyang Li, Yiwen Hu, Jun Wei +1
Existing polyp segmentation models are limited by high labeling costs and the small size of datasets. Additionally, vast polyp datasets remain underutilized because these models ty…
MixPolyp: Integrating Mask, Box and Scribble Supervision for Enhanced Polyp Segmentation
Yiwen Hu, Jun Wei, Yuncheng Jiang +4
Limited by the expensive labeling, polyp segmentation models are plagued by data shortages. To tackle this, we propose the mixed supervised polyp segmentation paradigm (MixPolyp).…
Let Video Teaches You More: Video-to-Image Knowledge Distillation using DEtection TRansformer for Medical Video Lesion Detection
Yuncheng Jiang, Zixun Zhang, Jun Wei +5
AI-assisted lesion detection models play a crucial role in the early screening of cancer. However, previous image-based models ignore the inter-frame contextual information present…
Generalize Polyp Segmentation via Inpainting across Diverse Backgrounds and Pseudo-Mask Refinement
Jiajian Ma, Fangqi Lu, Silin Huang +2
Inpainting lesions within different normal backgrounds is a potential method of addressing the generalization problem, which is crucial for polyp segmentation models. However, seam…
ECC-PolypDet: Enhanced CenterNet with Contrastive Learning for Automatic Polyp Detection
Yuncheng Jiang, Zixun Zhang, Yiwen Hu +6
Accurate polyp detection is critical for early colorectal cancer diagnosis. Although remarkable progress has been achieved in recent years, the complex colon environment and concea…
ScribblePolyp: Scribble-Supervised Polyp Segmentation through Dual Consistency Alignment
Zixun Zhang, Yuncheng Jiang, Jun Wei +2
Automatic polyp segmentation models play a pivotal role in the clinical diagnosis of gastrointestinal diseases. In previous studies, most methods relied on fully supervised approac…