Eero
Lehtonen
Senior Researcher, Turku PET Centre
D.Sc.(Tech.)
Links
Areas of expertise
Computer and machine vision
sensor fusion
Biography
Eero Lehtonen received the M.Sc. degree in mathematics and the D.Sc. (Tech.) degree in electronics from the University of Turku, in 2006 and 2013, respectively. He is currently working as a Senior Researcher with the Digital Health Technology Group, Department of Computing, University of Turku, Finland, where his research interests include computer vision and medical imaging. He has also worked in several companies as a machine vision specialist.
Research
Computer vision and sensor fusion for improving biomedical diagnostics and medical imaging.
Publications
Expanding interpretability through complexity reduction in machine learning‐based modelling of cardiovascular disease: A myocardial perfusion imaging PET/CT prognostic study (2025)
European Journal of Clinical Investigation
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )
Incremental prognostic value of downstream positron emission tomography perfusion imaging after coronary computed tomography angiography: a study using machine learning (2024)
EHJ Cardiovascular Imaging / European Heart Journal - Cardiovascular Imaging
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )
Deep generative denoising networks enhance quality and accuracy of gated cardiac PET data (2024)
Annals of Nuclear Medicine
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )
Incremental prognostic value of downstream PET perfusion imaging after coronary CT angiography (2023)
EHJ Cardiovascular Imaging / European Heart Journal - Cardiovascular Imaging
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )
Effect of respiratory motion correction and CT-based attenuation correction on dual-gated cardiac PET image quality and quantification (2022)
Journal of Nuclear Cardiology
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))
Synthetization, Distortion, and Geometric Correction of Isoelectric Focusing Gels for Newborn Screening (2022)
IEEE Access
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )
A Respiratory Motion Estimation Method Based on Inertial Measurement Units for Gated Positron Emission Tomography (2021)
Sensors
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))
Validation of Automated PET Segmentation Methods Based on Connected Components for Myocardium (2021)
IEEE Nuclear Science Symposium and Medical Imaging Conference, IEEE Nuclear Science Symposium and Medical Imaging Conference record
(Vertaisarvioitu artikkeli konferenssijulkaisussa (A4))
Learning to Denoise Gated Cardiac PET Images Using Convolutional Neural Networks (2021)
IEEE Access
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))
Estimation of optimal number of gates in dual gated F-18-FDG cardiac PET (2020)
Scientific Reports
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))