Teemu-Taneli Sahlström
Postdoctoral Researcher
Academy research fellow
Department of Technical Physics, Faculty of Science, Forestry and Technology
Research of Teemu Sahlström focuses on medical and biomedical tomographic imaging techniques utilising coupled physics. In his research, he develops numerical methods for modelling and inverse problem of tomographic imaging techniques utilising Bayesian framework for inverse problems, numerical modelling of physics, and deep learning.
Research groups
Research interests
- Thermo- and photoacoustic imaging
- Computational physics and inverse problems
- Imaging utilising coupled physics
- Electromagnetic and ultrasound modelling
- Deep learning
Files
2 itemsPublications
16/16 items-
Estimation of dielectric parameters from ultrasound waves in quantitative thermoacoustic tomography
Sahlström, Teemu; Tarvainen, Tanja, 2026, Measurement science and technology, 37, 17, 175401. A1 Journal article (refereed), original research -
Fast reconstruction approaches for photoacoustic tomography with smoothing Sobolev/Matérn priors
Kultima, Jaakko; Ramlau, Ronny; Sahlstrom, Teemu; Tarvainen, Tanja, 2026, Inverse problems and imaging, 25, 51-66. A1 Journal article (refereed), original research -
Comparative Analysis of Acoustic Reconstruction Methods for Chromophore and Oxygenation Quantification in Limited-View 3D Quantitative Photoacoustic Tomography
Tang, Guo; Lucka, Felix; Sahlström, Teemu; Cox, Ben; Tarvainen, Tanja; Laufer, Jan, 2025, Proceedings European Conferences on Biomedical Optics 2025. B3 Non-refereed conference proceedings -
Estimation of dielectric parameters in quantitative thermoacoustic tomography
Sahlström, Teemu; Lähivaara, Timo; Tarvainen, Tanja, 2025, Proceedings European Conferences on Biomedical Optics 2025. B3 Non-refereed conference proceedings -
Simultaneous estimation of electrical conductivity and permittivity in quantitative thermoacoustic tomography
Sahlström, Teemu; Lähivaara, Timo; Tarvainen, Tanja, 2025, Inverse problems, 41, 3, 035015. A1 Journal article (refereed), original research -
Utilizing uncertainty quantification variational autoencoders in inverse problems with applications in photoacoustic tomography
Goh, Hwan; Sahlström, Teemu; Tarvainen, Tanja, 2024, Bubba, Tatiana A, Data-driven Models in Inverse Problems, 413-436. A3 Book section, Chapters in research books -
Assembly of fluorophore J-aggregates with nanospacer onto mesoporous nanoparticles for enhanced photoacoustic imaging
Xu, Wujun; Leskinen, Jarkko; Sahlström, Teemu; Happonen, Emilia; Tarvainen, Tanja; Lehto, Vesa-Pekka, 2023, Photoacoustics, 33, 100552. A1 Journal article (refereed), original research -
Computational methods for modelling and inverse problem of photoacoustic tomography
Sahlström, Teemu, 2023, Publications of the University of Eastern Finland. Dissertations in Science, Forestry and Technology. G5 Doctoral dissertation (article) -
Deep learning in photoacoustic tomography utilizing variational autoencoders
Sahlström, Teemu; Tarvainen, Tanja, 2023, Kim, Chulhong; Laufer, Jan; Ntziachristos, Vasilis: Zemp, Roger J, Opto-Acoustic Methods and Applications in Biophotonics VI. A4 Conference proceedings -
Utilizing Variational Autoencoders in the Bayesian Inverse Problem of Photoacoustic Tomography
Sahlström, Teemu; Tarvainen, Tanja, 2023, Siam journal on imaging sciences, 16, 1, 89-110. A1 Journal article (refereed), original research