Publications

Publications

• J. Lahtinen, A. Koulouri, A. Rezaei, S. Pursiainen, Conditionally Exponential Prior in Focal Near- and Far-Field EEG Source Localization via Randomized Multiresolution Scanning (RA-MUS) (Accepted in Journal of Mathematical Imaging and Vision, 2022)

• A. Koulouri, Real-time Ionospheric Imaging of S4 Scintillation from Limited Data with Parallel Kalman Filters and Smoothness,  vol. 60, pp. 1-12, 2022, Art no. 4106012, doi:10.1109/T GRS.2022.3140600 (ver. 1 arXiv: 2105.05360)

•  A. Rezaei, J. Lahtinen, F. Neugebauer, M. Antonakakis, M.C. Piastra, A. Koulouri A, C. H. Wolters, S. Pursiainen. Reconstructing subcortical and cortical somatosensory activity via the RAMUS inverse source analysis technique using median nerve SEP data. Neuroimage. 2021 Dec 15;245:118726. doi:10.1016/j.neuroimage.2021.11872 

• A. Koulouri, P. Heins and M. Burger, "Adaptive Superresolution in Deconvolution of Sparse Peaks," in IEEE Transactions on Signal Processing, vol. 69, pp. 165-178, 2021, doi: 10.1109/TSP.2020.3037373. 

• A. Koulouri, V. Rimpilainen Simultaneous Skull Conductivity and Focal Source Imaging from EEG Recordings with the help of Bayesian Uncertainty Modelling  ( arXiv:2002.00066)

• V. Rimpilainen, Th. Samaras, A. Koulouri, Electrical Impedance Tomography with Box Constraint for Skull Conductivity Estimation ( arXiv:2001.11830)

• Rezaei, A., Koulouri, A. & Pursiainen, S.,Randomized Multiresolution Scanning in Focal and Fast E/MEG Sensing of Brain Activity with a Variable Depth, Mar 2020, In : Brain Topography. 33, 2, p. 161-175

• A. Koulouri, V. Rimpiläinen and N. Smith, Position Dilution of Precision and Bayesian Model of the Observation Error ( 2020arXiv:2001.02198)

•  A. Koulouri, N.D. Smith,  B.C.Vani, B. C.,  V.J.T Rimpiläinen, I. Astin, &  B. Forte,  Methodology to estimate ionospheric scintillation risk maps and their contribution to position dilution of precision on the ground, In : Journal of Geodesy 94, 2, 2020

• V. Rimpiläinen, A. Koulouri, F. Lucka, J.P. Kaipio, C.H. Wolters Improved EEG source localization with Bayesian uncertainty modelling of unknown skull conductivity, NeuroImage,188, 252-256, 2019

• A. Koulouri, V. Rimpiläinen, M. Brookes. J.P. Kaipio, Prior Variances and Depth Un-biased Estimators in EEG Focal source Imaging, arXiv:1703.09044 

• V. Rimpiläinen,  A. Koulouri, F. Lucka, J.P. Kaipio, C.H. Wolters, Bayesian Modelling of Skull Conductivity Uncertainties in EEG Source Imaging, arXiv:1703.09031

• A. Koulouri, M. Brookes and V. Rimpilainen. Vector tomography for reconstructing electric Fieldwith non-zero divergence in bounded domains, Journal of Computational Physic,329, 15 January 2017, Pages 73–90

• A. Koulouri, V. Rimpilainen, M. Brookes and J. P. Kaipio. Compensation of domain modelling errors in the inverse source problem of the Poisson equation: application in electroencephalographic imaging, Applied Numerical Mathematics, Vol. 106, Aug. 2016, P. 24-36 (download the original version click here)

• A. Koulouri, M. Petrou. Vector Field Tomography: Reconstruction of an Irrotational Field in the Discrete Domain.

• DOI: 10.2316/P.2012.778-021, Proceeding (778) Signal Processing, Pattern Recognition and Applications / 779: Computer Graphics and Imaging - 2012  (download an older version)

 Reports

• A.Koulouri, M. Petrou. Stable Reconstruction of Irrotational Vector Fields based onthe Discrete Longitudinal Ray Transform.

• A.Koulouri, M. Petrou. Automatic segmentation of the abdominal Aorta from CT images, LAP Lambert Academic Publishing, 2011.

Thesis

• (2012)  PhD Transfer Report: Vector Field Tomography (download)

• (2015)  PhD Thesis (2015): Reconstruction of Electric Fields and Source Distributions in EEG Brain Imaging  download here:  https://spiral.imperial.ac.uk/handle/10044/1/25759

• (2009) Thoracic Organ Segmentation for RT Planning (download)

• (2008) Automatic Segmentation and 3D Reconstruction of the abdominal aorta (download)

Presentations

• Talk on '' Knowledge-based learning for model parameter selection in linear inverse problems''  Centre for Mathematics and Algorithms for Data (MAD), Maths Dept., University of Bath, 21.2.2024 (invited by Dr. Yury Korolev). 

• Talk on Model-based Learning in Linear Inverse Problems, in Applied Math Seminar, Tampere University, 27.10.2023

•  Talk on “Bayesian Machine Learning for Model Parameter Selection in Inverse Problems: Application in Personalized Brain Activity Imaging “, Tampere Imaging Days 2023, 15. - 16. June, 2023

•  Talk real time imaging of ionospheric scintillation, 27.6.2022,  invited by Prof. Galera- Monico (Sao Paolo State University) 

• Real-time Ionospheric Imaging of Scintillation from Limited Data with Parallel Kalman Filters, Inverse Days, Tampere FI 2021 

• Presentation of my work Super-resolution in Sparse Peak deconvolution on discrete grids with applications in spectroscopy and microscopy  in Morpheme group meeting, Inria Sophia Antipolis - Tuesday April 20, 2021 (https://team.inria.fr/morpheme/contacts/) (invited by Dr. Luca Calatroni)

• Skull Conductivity and Focal Source Imaging from EEG Recordings with the help of Bayesian Uncertainty Modelling, NonInvasive Mathematics On-line INDAM Workshop  April 13-16 2021 (invited speaker)

• Compensating model uncertainties and effects of reduced order models in EEG source imaging by using Bayesian statistics: UNCECOMP 2019, 24-26 June 2019, Crete, Greece

• Presentation of project PEBI, 20-21 May 2019, Kick-off meeting for ATTRACT Funded projects, Cern Switzerland

• “Improved source estimation in EEG with Bayesian modelling of the unknown skull conductivity”  SIAM Conference on IMAGING SCIENCE June 5-8, 2018 Bologna - Italy

• Prior Variances and Depth Un-Biased Estimators in EEG Focal Source Imaging, EMBEC conference, Tampere June 11-15, 2017

• Towards the reconstruction of electric fields produced by focal brain sources with the help of vector tomography: Linz, 27-31/3/2017,100 Years of the Radon Transform - Ricam (invited by Prof. Th. Schuster)

• Inverse Days, 13-15 Dec. 2016: Kuopio Dec 2016: Super-resoltuon in sparse peak deconvolution with applications in fluorescence microscopy

• Mathematical Imaging and Emerging Modalityies: Osnabruck 27-30/6/2016: Super-resolution in sparse peak deconvolution on discrete grids

• Copenhagen HD Tomo Days: 6/4/2016 - 8/4/2016 : Reconstruction of Electric Field with non-zero divergence using Vector Tomography

• Kaiserslautern Meeting Dec. 2015:  Super-resolution in sparse spike deconvolution

•  Inverse Days, Tampere, Dec. 9-11, 2014, Compensation of Modelling Errors in EEG Source Imaging using Bayesian Statistics

• Stable Reconstruction of Irrotational Vector Fields using Longitudinal Line Integrals, NZ Maths and Stats. Postgraduate Conference (NZMASP) Nov. 12-16, ​2012, Auckland

• Vector Field Tomography: Reconstruction of an Irrotational Field in the Discrete Domain,    IASTED International Conference on SPPRA, June 18-20, 2012, CRETE, (track code: 778-021)

Training

ESADE: ATTRACT Introductory Crash Course in Entrepreneurship, Barcelona, 21-24 Oct. 2019 (32 hours)