9 papers
3D Uncertainty Quantification for the Photo-Acoustic Tomography
Babak Maboudi Afkham, Amal Mohammed A Alghami, Hassan Yazdanian +1
Photoacoustic tomography (PAT) is a promising modality for high-resolution biomedical imaging, motivating the need for reliable uncertainty quantification (UQ) of reconstructed ima…
Adjoint-Based Bayesian Uncertainty Quantification for PDE-Constrained Inverse Problems with Application to Semiconductor Imaging
Hassan Yazdanian, Leila Taghizadeh, Babak Maboudi Afkham
We formulate a Bayesian framework for reconstructing doping profiles in pn-junction semiconductor devices from boundary flux measurements. The unknown doping field is modeled as a…
QVaR: a Quantum Variational Regularization method for Linear Inverse Problems
Siiri Rautio, Hjørdis Schlüter, Andreas Hauptmann +1
We present a tailored framework for solving regularized linear inverse problems using quantum optimization methods. By discretizing the solution space and encoding data fidelity an…
Simultaneous Estimation of Seabed and Its Roughness With Longitudinal Waves
Babak Maboudi Afkham, Ana Carpio
This paper introduces an infinite-dimensional Bayesian framework for acoustic seabed tomography, leveraging wave scattering to simultaneously estimate the seabed and its roughness.…
Bayesian Formulation of Acousto-Electric Tomography and Quantified Uncertainty in Limited View
Hjørdis Schlüter, Babak Maboudi Afkham
Acousto-electric tomography (AET) is a hybrid imaging modality that combines electrical impedance tomography with focused ultrasound perturbations to obtain interior power density…
Bayesian decomposition using Besov priors
Andreas Horst, Babak Maboudi Afkham, Yiqiu Dong +1
In many inverse problems, the unknown is composed of multiple components with different regularities, for example, in imaging problems, where the unknown can have both rough and sm…