Remote sensing image semantic segmentation, which aims to realize pixel-level classification according to the content of remote sensing images, has broad applications in various fields. Thanks to the ...

Despite the remarkable progress in semi-supervised medical image segmentation methods based on deep learning, their application to real-life clinical scenarios still faces considerable challenges. For ...

The triggering receptor expressed on myeloid cells 2 (TREM2) plays a pivotal role in the activation of myeloid cells and is ...

Self-supervised deep learning models can accurately perform 3D segmentation of cell nuclei in complex biological tissues, enabling scalable analysis in settings with limited or no ground truth ...