6 citations · 13 across the 13 of their papers we have counts for
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Inferring Object Boundaries and their Roughness with Uncertainty Quantification
Babak Maboudi Afkham, Nicolai André Brogaard Riis, Yiqiu Dong +1
This work describes a Bayesian framework for reconstructing the boundaries that represent targeted features in an image, as well as the regularity (i.e., roughness vs. smoothness)…
Uncertainty Quantification of Inclusion Boundaries in the Context of X-ray Tomography
Babak Maboudi Afkham, Yiqiu Dong, Per Christian Hansen
In this work, we describe a Bayesian framework for reconstructing the boundaries of piecewise smooth regions in the X-ray computed tomography (CT) problem in an infinite-dimensiona…
Fixing Nonconvergence of Algebraic Iterative Reconstruction with an Unmatched Backprojector
Yiqiu Dong, Per Christian Hansen, Michiel E. Hochstenbach +1
We consider algebraic iterative reconstruction methods with applications in image reconstruction. In particular, we are concerned with methods based on an unmatched projector/backp…
Tomographic Reconstruction with Spatially Varying Parameter Selection
Yiqiu Dong, Carola-Bibiane Schönlieb
In this paper we propose a new approach for tomographic reconstruction with spatially varying regularization parameter. Our work is based on the SA-TV image restoration model propo…
Directional Total Generalized Variation Regularization
Rasmus Dalgas Kongskov, Yiqiu Dong, Kim Knudsen
In inverse problems, prior information and a priori-based regularization techniques play important roles. In this paper, we focus on image restoration problems, especially on resto…
Bregman Cost for Non-Gaussian Noise
Martin Burger, Yiqiu Dong, Federica Sciacchitano
One of the tasks of the Bayesian inverse problem is to find a good estimate based on the posterior probability density. The most common point estimators are the conditional mean (C…