5 papers
Bayesian Joint Reconstruction and Uncertainty Quantification for Limited-Data Multi-Contrast X-Ray CT
Hassan Yazdanian, Henrik Mäkinen
Multi-contrast X-ray computed tomography (CT) combines attenuation contrast with phase and dark-field contrast, which are sensitive to refraction and ultra-small-angle scattering,…
3D Uncertainty Quantification for Photoacoustic 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…
Solving the MIT Inverse Problem by Considering Skin and Proximity Effects in Coils
Hassan Yazdanian, Reza Jafari, Hamid Abrishami Moghaddam
This paper presents an improved technique for solving the inverse problem in magnetic induction tomography (MIT) by considering skin and proximity effects in coils. MIT is a non-co…
Improved Forward Problem Modeling in Magnetic Induction Tomography for Biomedical Applications
Hassan Yazdanian
The main contribution of this thesis is to investigate the incorporating skin and proximity effects in magnetic induction tomography (MIT) coils and present an improved model for t…