Uncertainty-Aware Adapter: Adapting Segment Anything Model (SAM) for Ambiguous Medical Image Segmentation

16 March 2024

Papers citing "Uncertainty-Aware Adapter: Adapting Segment Anything Model (SAM) for Ambiguous Medical Image Segmentation"

4 / 4 papers shown

Title
UncertainSAM: Fast and Efficient Uncertainty Quantification of the Segment Anything Model T. Kaiser Thomas Norrenbrock Bodo Rosenhahn 42 0 0 08 May 2025
Probabilistic 3D segmentation for aleatoric uncertainty quantification in full 3D medical data Christiaan G. A. Viviers Amaan Valiuddin Peter H. N. de With Fons van der Sommen 15 4 0 01 May 2023
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 258 7,337 0 11 Nov 2021
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 229 74,467 0 18 May 2015