Enhancing global sensitivity and uncertainty quantification in medical image reconstruction with Monte Carlo arbitrary-masked mamba

Jiahao Huang, Liutao Yang, Fanwen Wang, Yinzhe Wu, Yang Nan, Weiwen Wu, Chengyan Wang, Kuangyu Shi, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Daoqiang Zhang, Guang Yang

Abstract: Highlights•A novel Mamba-based model for medical image reconstruction and uncertainty estimation.•The proposed model has global sensitivity and linear computational complexity.•A novel arbitrary masked module for uncertainty estimation without performance drop.•The performance achieves SOTA on fast MRI, sparse-view CT and low-dose PET.