World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
38
Citations
5390
World Ranking
2372
National Ranking
14

Engineering and Technology

D-Index
40
Citations
5901
World Ranking
7382
National Ranking
48

Overview

Ville Kolehmainen is affiliated with the University of Eastern Finland in Finland. Their research spans the fields of Engineering and Medicine, with a particular focus on Radiology, Nuclear Medicine and Imaging, Electrical and Electronic Engineering, Biomedical Engineering, Geophysics, and Global and Planetary Change.

The scientist's work covers diverse topics including Electrical and Bioimpedance Tomography, Advanced MRI Techniques and Applications, Medical Imaging Techniques and Applications, Geophysical and Geoelectrical Methods, Sparse and Compressive Sensing Techniques, Flow Measurement and Analysis, and Atmospheric chemistry and aerosols.

Frequent co-authors in their publications include:

  • J. Toivanen
  • Marko Vauhkonen
  • Matti Hanhela
  • Antti Lipponen
  • A. Hänninen

Common venues for their published research comprise:

  • arXiv (Cornell University)
  • Atmospheric measurement techniques
  • Inverse Problems and Imaging
  • Journal of Imaging
  • Journal of Mathematical Imaging and Vision

Selected recent papers include:

  • Nonstationary Image Reconstruction in Ultrasonic Transmission Tomography Using Kalman Filter and Dimension Reduction, 2020, IEEE Transactions on Instrumentation and Measurement
  • Deep-learning-based post-process correction of the aerosol parameters in the high-resolution Sentinel-3 Level-2 Synergy product, 2022, Atmospheric measurement techniques
  • Joint Reconstruction of Conductivity and Velocity in Two-Phase Flows Using Electromagnetic Flow Tomography and Electrical Tomography: A Simulation Study, 2021, IEEE Transactions on Instrumentation and Measurement
  • OMEGA-open-source emission tomography software, 2021, Physics in Medicine and Biology
  • Model-enforced post-process correction of satellite aerosol retrievals, 2021, Atmospheric measurement techniques

Best Publications

  • Statistical inversion and Monte Carlo sampling methods in electrical impedance tomography

    Jari P Kaipio;Ville Kolehmainen;Erkki Somersalo;Marko Vauhkonen

  • Inverse problems with structural prior information

    J P Kaipio;V Kolehmainen;M Vauhkonen;E Somersalo

  • Approximation errors and model reduction with an application in optical diffusion tomography

    S R Arridge;J P Kaipio;V Kolehmainen;M Schweiger

  • Statistical inversion for medical x-ray tomography with few radiographs: I. General theory

    S Siltanen;V Kolehmainen;S Järvenpää;J P Kaipio

  • Assessment of errors in static electrical impedance tomography with adjacent and trigonometric current patterns.

    V Kolehmainen;M Vauhkonen;P A Karjalainen;J P Kaipio

  • RECOVERY OF REGION BOUNDARIES OF PIECEWISE CONSTANT COEFFICIENTS OF AN ELLIPTIC PDE FROM BOUNDARY DATA

    V Kolehmainen;S R Arridge;W R B Lionheart;M Vauhkonen

  • Compensation of Modelling Errors Due to Unknown Domain Boundary in Electrical Impedance Tomography

    A Nissinen;V P Kolehmainen;J P Kaipio

  • Coupled radiative transfer equation and diffusion approximation model for photon migration in turbid medium with low-scattering and non-scattering regions.

    Tanja Tarvainen;Marko Vauhkonen;Ville Kolehmainen;Simon R Arridge

  • Statistical inversion for medical x-ray tomography with few radiographs: II. Application to dental radiology.

    V. Kolehmainen;S. Siltanen;Seppo Järvenpää;J. Kaipio

  • Dynamic Physiological Modeling for Functional Diffuse Optical Tomography

    Solomon Gilbert Diamond;Theodore J. Huppert;Ville Kolehmainen;Maria Angela Franceschini

  • Time-series estimation of biological factors in optical diffusion tomography

    Simon Prince;Ville Kolehmainen;Jari P Kaipio;Maria Angela Franceschini;Maria Angela Franceschini

  • Compensation of errors due to discretization, domain truncation and unknown contact impedances in electrical impedance tomography

    A Nissinen;L M Heikkinen;V Kolehmainen;J P Kaipio

  • PET Reconstruction With an Anatomical MRI Prior Using Parallel Level Sets

    Matthias J. Ehrhardt;Pawel Markiewicz;Maria Liljeroth;Anna Barnes

  • Hybrid radiative-transfer-diffusion model for optical tomography.

    Tanja Tarvainen;Marko Vauhkonen;Ville Kolehmainen;Jari P. Kaipio

  • Three-dimensional reconstruction of shape and piecewise constant region values for optical tomography using spherical harmonic parametrization and a boundary element method

    Athanasios D Zacharopoulos;Simon R Arridge;Oliver Dorn;Ville Kolehmainen

  • Finite element model for the coupled radiative transfer equation and diffusion approximation

    T. Tarvainen;M. Vauhkonen;V. Kolehmainen;J. P. Kaipio

  • The Inverse Conductivity Problem with an Imperfectly Known Boundary

    Ville Kolehmainen;Matti Lassas;Petri Ola

  • RECONSTRUCTION OF DOMAIN BOUNDARY AND CONDUCTIVITY IN ELECTRICAL IMPEDANCE TOMOGRAPHY USING THE APPROXIMATION ERROR APPROACH

    Antti Nissinen;Ville Kolehmainen;Jari P. Kaipio

  • An approximation error approach for compensating for modelling errors between the radiative transfer equation and the diffusion approximation in diffuse optical tomography

    T Tarvainen;T Tarvainen;V Kolehmainen;A Pulkkinen;A Pulkkinen;M Vauhkonen

  • MARGINALIZATION OF UNINTERESTING DISTRIBUTED PARAMETERS IN INVERSE PROBLEMS-APPLICATION TO DIFFUSE OPTICAL TOMOGRAPHY

    Kolehmainen;T Tarvainen;Arridge;Jari Kaipio

Frequent Co-Authors

Jari P. Kaipio
Jari P. Kaipio University of Auckland
Simon R. Arridge
Simon R. Arridge University College London
Marko Vauhkonen
Marko Vauhkonen University of Eastern Finland
Matti Lassas
Matti Lassas University of Helsinki
Martin Schweiger
Martin Schweiger University College London
Erkki Somersalo
Erkki Somersalo Case Western Reserve University
Olli Gröhn
Olli Gröhn University of Eastern Finland
David A. Boas
David A. Boas Boston University
Renato M. Cotta
Renato M. Cotta Federal University of Rio de Janeiro
Theodore J. Huppert
Theodore J. Huppert University of Pittsburgh

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