The detection and resection of small polyp objects in colonoscopy images are of great
significance for the prevention of colorectal cancer (CRC). At present, blurred edges …

Although unsupervised domain adaptation (UDA) is a promising direction to alleviate
domain shift, they fall short of their supervised counterparts. In this work, we investigate …

Accurate polyp segmentation plays a critical role from colonoscopy images in the diagnosis
and treatment of colorectal cancer. While deep learning-based polyp segmentation models …

Deep polyp segmentation methods have made tremendous progress recently. However,
due to the domain shift among different imaging modalities, existing methods learned on …

Colorectal polyp segmentation (CPS), an essential problem in medical image analysis, has
garnered growing research attention. Recently, the deep learning-based model completely …

Accurate segmentation of polyps in colonoscopy images is important for the prevention and
treatment of colorectal cancer. However, samples collected from different centers often …

Cross-domain joint segmentation of optic disc and optic cup on fundus images is essential,
yet challenging, for effective glaucoma screening. Although many unsupervised domain …

Accuratelysegmenting polyps from colonoscopy images is essential for diagnosing
colorectal cancer. Despite the tremendous success of the deep convolutional neural …

Deep neural networks have shown promising performance for automatic segmentation of
Gross Tumor Volume (GTV) of Nasopharyngeal Carcinoma (NPC). However, models trained …