5 papers
Enabling self-supervised learned primal dual with Noise2Inverse
Antti Sällinen, Siiri Rautio, Santeri Kaupinmäki +1
X-ray computed tomography reconstruction is an ill-posed inverse problem, particularly in low-dose and sparse-angle settings where measurements are noisy and incomplete. While lear…
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…
Complex Wavelet-Based Sinogram Segmentation for Metal Artifact Reduction in Cone-Beam CT
Siiri Rautio, Alexander Meaney, Salla-Maaria Latva-Äijö +5
Metal objects pose a significant challenge in cone-beam computed tomography, as their strong and energy-dependent X-ray attenuation leads to inconsistent projections and severe str…
Learned enclosure method for experimental EIT data
Sara Sippola, Siiri Rautio, Andreas Hauptmann +2
Electrical impedance tomography (EIT) is a non-invasive imaging method with diverse applications, including medical imaging and non-destructive testing. The inverse problem of reco…
Stroke classification using Virtual Hybrid Edge Detection from in silico electrical impedance tomography data
Juan Pablo Agnelli, Fernando S. Moura, Siiri Rautio +4
Electrical impedance tomography (EIT) is a non-invasive imaging method for recovering the internal conductivity of a physical body from electric boundary measurements. EIT combined…