Meta’s open-source AI models SAM 3 and DINOv3 are running on 300 NVIDIA A100 GPUs at Lawrence Berkeley National Lab, ...
Abstract: Image segmentation, a fundamental problem in image processing, involves distinguishing the foreground from the background. Traditional image segmentation methods are typically divided into ...
[1] F. Shu, et al. "Structure PLP-SLAM: Efficient Sparse Mapping and Localization using Point, Line and Plane for Monocular, RGB-D and Stereo Cameras". IEEE ...
A major challenge in the analysis of tissue imaging data is cell segmentation, the task of identifying the precise boundary of every cell in an image. To address this problem we constructed TissueNet, ...
Neuromuscular disorders are rare diseases for which few therapeutic strategies currently exist. Assessment of therapeutic strategies efficiency is limited by the lack of biomarkers sensitive to the ...
Segmentation and 3D reconstruction of the human atria is of crucial importance for precise diagnosis and treatment of atrial fibrillation, the most common cardiac arrhythmia. However, the current ...
The accurate modeling of the liver vessel network structure is an important prerequisite for developing a preoperative plan for the liver. Considering that extracting liver blood vessels from ...
Abstract: Medical image segmentation is a fundamental and challenging problem for analyzing medical images. Among different existing medical image segmentation methods, graph-based approaches are ...
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