The team of Professor Tanja Tarvainen investigates and develops computational methods for optical and ultrasonic inverse problems such as tomographic imaging and therapy in the framework of Bayesian inverse problems. The tomographic methods include purely light based modalities such as diffuse optical tomography and coupled physics imaging such as photoacoustic tomography. In addition, modelling and computational methods for light transport and ultrasound propagation are studied, and prototype instrumentation for the techniques are developed.
Research groups
Research groups
- Computational Physics and Inverse Problems Group
- Biomedical Optical Imaging and Ultrasound Laboratory (OPUS)
- Institute of Photonics
- Visiting Professor, Department of Computer Science, University College London, UK
- Collaborator in CUQI – Computational Uncertainty Quantification for Inverse Problems, DTU Compute, Denmark
Projects
- Quantitative Tomography Using Coupled Physics of Waves (QUANTOM), ERC-CoG project, 2021-2025
- COmputatioNal Imaging as a training Network for Smart biomedical dEvices (CONcISE), Marie Skłodowska-Curie Actions – Doctoral Networks, 2023-2027
- Centre of Excellence in Inverse Modelling and Imaging, Academy of Finland, 2018-2025
- PREIN – the Finnish Flagship on Photonics Research and Innovation
- Nanotheranostics based on light, RADDESS Academy Programme, Academy of Finland, 2018-2021
Research interests
- ValoMC – a Monte Carlo software and MATLAB toolbox for simulating light transport in biological tissue
- Inverse problems
- Uncertainty quantification
- Optical tomography
- Photoacoustic tomography
- Radiative transfer
Teaching Activities
- Current teaching: Optimisation
- Past teaching (lectures): Finite element methods, Modelling II, Tieteellinen viestintä fysiikassa
- Past teaching (exercises): Statistical inverse problems, Mathematical modelling, Finite element methods, Optimization, Estimation theory, Modelling II, Physics A, Physics III
Files
3 itemsPublications
118 items-
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: -
Deep learning in photoacoustic tomography utilizing variational autoencoders
Sahlström, Teemu; Tarvainen, Tanja. Teoksessa: Kim, Chulhong; Laufer, Jan; Ntziachristos, Vasilis: Zemp, Roger J(toim.) , 2023. Opto-Acoustic Methods and Applications in Biophotonics VI. s. . SPIE -
Diffuse optical tomography setup using a nanosecond laser
Mozumder, Meghdoot; Leskinen, Jarkko; Tarvainen, Tanja. 2023. -
Image reconstruction in quantitative photoacoustic tomography using adaptive optical Monte Carlo
Hänninen, Niko; Pulkkinen, Aki; Arridge, Simon R; Tarvainen, Tanja. Teoksessa: Oraevsky, Alexander A; Wang, Lihong V(toim.) , 2023. Photons Plus Ultrasound: Imaging and Sensing 2023. s. . SPIE -
One-step estimation of spectral optical parameters in quantitative photoacoustic tomography
Suhonen, Miika; Pulkkinen, Aki; Tarvainen, Tanja. Teoksessa: Kim, Chulhong; Laufer, Jan; Ntziachristos, Vasilis: Zemp, Roger J(toim.) , 2023. Opto-Acoustic Methods and Applications in Biophotonics VI. s. . SPIE -
Utilizing Variational Autoencoders in the Bayesian Inverse Problem of Photoacoustic Tomography
Sahlström, Teemu; Tarvainen, Tanja. 2023. Siam journal on imaging sciences. 16: 89-110 -
Utilizing variational autoencoders in photoacoustic tomography
Sahlström, Teemu; Tarvainen, Tanja. Teoksessa: Oraevsky, Alexander; Wang, Lihong(toim.) , 2023. Photons Plus Ultrasound: Imaging and Sensing 2023. s. . SPIE -
A model-based iterative learning approach for diffuse optical tomography
Mozumder, Meghdoot; Hauptmann, Andreas; Nissilä, Ilkka; Arridge, Simon R.; Tarvainen, Tanja. 2022. IEEE transactions on medical imaging. 41: 1289-1299 -
Adaptive stochastic Gauss–Newton method with optical Monte Carlo for quantitative photoacoustic tomography
Hänninen, Niko; Pulkkinen, Aki; Arridge, Simon; Tarvainen, Tanja. 2022. Journal of biomedical optics. 27: -
Diffuse optical tomography utilizing model-based learning
Mozumder, Meghdoot; Hauptmann, Andreas; Arridge, Simon R.; Tarvainen, Tanja. Teoksessa: (toim.) , 2022. Biophotonics Congress: Biomedical Optics 2022. s. . Optical Society of America