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Found 4 papers, 4 papers with code
Indescribable Multi-modal Spatial Evaluator
IMSE creates an accurate multi-modal spatial evaluator to measure spatial differences between two images, and then optimizes registration by minimizing the error predicted of the evaluator.
XBound-Former: Toward Cross-scale Boundary Modeling in Transformers
Skin lesion segmentation from dermoscopy images is of great significance in the quantitative analysis of skin cancers, which is yet challenging even for dermatologists due to the inherent issues, i. e., considerable size, shape and color variation, and ambiguous boundaries.
Breaking the Dilemma of Medical Image-to-image Translation
In order to break the dilemma of the existing modes, we propose a new unsupervised mode called RegGAN for medical image-to-image translation.
Boundary-aware Transformers for Skin Lesion Segmentation
Skin lesion segmentation from dermoscopy images is of great importance for improving the quantitative analysis of skin cancer.
Ranked #5 on
Lesion Segmentation
on ISIC 2018
