⭐ Let's have a quick recap of our main idea. Full-screen viewing is recommended for better visual details. lawdis_show_quick_v5_small.mov We present LawDIS, a language-window-based controllable ...

Abstract: Both limited annotation and domain shift are prevalent challenges in medical image segmentation. Traditional semi-supervised segmentation and unsupervised domain adaptation methods address ...

Abstract: The success of deep learning in 3D medical image segmentation hinges on training with a large dataset of fully annotated 3D volumes, which are difficult and time-consuming to acquire.

On Wednesday, Meta announced an AI model called the Segment Anything Model (SAM) that can identify individual objects in images and videos, even those not encountered during training, reports Reuters.