Automatic and accurate segmentation of pulmonary nodules in CT images can help
physicians perform more accurate quantitative analysis, diagnose diseases, and improve …

Contextual information has been shown to be powerful for semantic segmentation. This work
proposes a novel Context-based Tandem Network (CTNet) by interactively exploring the …

Computer-aided medical image segmentation has been applied widely in diagnosis and
treatment to obtain clinically useful information of shapes and volumes of target organs and …

Medical image segmentation plays an important role in computer-aided diagnosis. Attention
mechanisms that distinguish important parts from irrelevant parts have been widely used in …

Change detection (CD) remains an important issue in remote sensing applications,
especially for high-resolution images, but it has yet to be fully resolved. In this study, we …

Dental X-ray image segmentation is helpful for assisting clinicians to examine tooth
conditions and identify dental diseases. Fast and lightweight segmentation algorithms …

Surgical instrument segmentation plays a promising role in robot-assisted surgery. However,
illumination issues often appear in surgical scenes, altering the color and texture of surgical …

Minimally invasive surgeries and related applications demand surgical tool classification
and segmentation at the instance level. Surgical tools are similar in appearance and are …

Deep learning has achieved great success in areas such as computer vision and natural
language processing. In the past, some work used convolutional networks to process EEG …

Background Artificial intelligence aided tumor segmentation has been applied in various
medical scenarios and showed effectiveness in helping physicians observe the potential …