Researchers introduced Spatial Lifting (SL), a method that lifts 2D image inputs into a higher-dimensional space and processes them with networks such as a 3D U-Net, according to the arXiv paper 2610.…
Researchers introduced a GPU-accelerated framework for segmenting anisotropic 3D microscopy volumes without dense annotations, achieving accuracy matching inter-expert agreement. The method, applied t…
A new benchmark study from arXiv compares five deep learning models for 3D brain tumor segmentation from MRI, finding trade-offs between accuracy and efficiency. The study evaluated 3D U-Net, SegResNe…
Researchers introduced 4DHumanDiff, a diffusion framework that directly generates dynamic human assets represented by 4D Gaussian Splatting (4DGS) from text prompts, avoiding video pre-generation and …
Researchers have developed VesselSim, a two-stage framework for 3D blood vessel segmentation that eliminates the need for expert annotations during training by generating 16,500 synthetic angiographic…