 
				Teemu-Taneli Sahlström
Postdoctoral Researcher
Postdoctoral researcher
Department of Technical Physics, Faculty of Science, Forestry and Technology
Research of Teemu Sahlström focuses on developing numerical methods for imaging methods utilising coupled physics, such as photo- and thermoacoustic tomography. In his research, he utilises, for example, theory of Bayesian inverse problems, deep learning, and numerical physics and mathematics.
Research groups
Publications
12/12 items- 
																							
																									Simultaneous estimation of electrical conductivity and permittivity in quantitative thermoacoustic tomographySahlström, Teemu; Lähivaara, Timo; Tarvainen, Tanja, 2025, Inverse problems, 41, 3, 035015. A1 Journal article (refereed), original research
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																									Utilizing uncertainty quantification variational autoencoders in inverse problems with applications in photoacoustic tomographyGoh, Hwan; Sahlström, Teemu; Tarvainen, Tanja, 2024, Bubba, Tatiana A, Data-driven Models in Inverse Problems, 413-436. A3 Book section, Chapters in research books
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																									Assembly of fluorophore J-aggregates with nanospacer onto mesoporous nanoparticles for enhanced photoacoustic imagingXu, Wujun; Leskinen, Jarkko; Sahlström, Teemu; Happonen, Emilia; Tarvainen, Tanja; Lehto, Vesa-Pekka, 2023, Photoacoustics, 33, 100552. A1 Journal article (refereed), original research
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																									Computational methods for modelling and inverse problem of photoacoustic tomographySahlström, Teemu, 2023, Publications of the University of Eastern Finland. Dissertations in Science, Forestry and Technology. G5 Doctoral dissertation (article)
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																									Deep learning in photoacoustic tomography utilizing variational autoencodersSahlström, Teemu; Tarvainen, Tanja, 2023, Kim, Chulhong; Laufer, Jan; Ntziachristos, Vasilis: Zemp, Roger J, Opto-Acoustic Methods and Applications in Biophotonics VI. A4 Conference proceedings
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																									Utilizing Variational Autoencoders in the Bayesian Inverse Problem of Photoacoustic TomographySahlström, Teemu; Tarvainen, Tanja, 2023, Siam journal on imaging sciences, 16, 1, 89-110. A1 Journal article (refereed), original research
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																									Utilizing variational autoencoders in photoacoustic tomographySahlström, Teemu; Tarvainen, Tanja, 2023, Oraevsky, Alexander; Wang, Lihong, Photons Plus Ultrasound: Imaging and Sensing 2023. A4 Conference proceedings
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																									Computationally Efficient Forward Operator for Photoacoustic Tomography Based on Coordinate TransformationsSahlstrom, Teemu; Pulkkinen, Aki; Leskinen, Jarkko; Tarvainen, Tanja, 2021, IEEE transactions on ultrasonics ferroelectrics and frequency control, 68, 6, 2172-2182. A1 Journal article (refereed), original research
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																									Computationally efficient forward model for photoacoustic tomographySahlstrom, Teemu; Pulkkinen, Aki; Leskinen, Jarkko; Tarvainen, Tanja, 2021, Kim, Chuolhong; Laufer, Jan; Zemp, Roger J, Proc. SPIE, Opto-Acoustic Methods and Applications in Biophotonics V, 1192308. A4 Conference proceedings
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																									Modeling of Errors due to Uncertainties in Ultrasound Sensor Locations in Photoacoustic TomographySahlström, Teemu; Pulkkinen, Aki; Tick, Jenni; Leskinen, Jarkko; Tarvainen, Tanja, 2020, IEEE transactions on medical imaging, 39, 6, 2140-2150. A1 Journal article (refereed), original research
