Jakob Heydorn Lagerlöf
Position: Affiliated Researcher School/office: School of Medical SciencesEmail: jakob.heydorn-lagerlof@oru.se
Phone: No number available
Room: -
About Jakob Heydorn Lagerlöf
Jakob Heydorn Lagerlöf is a medical physicist, with a background in experimental physics and automotive engineering. He has university diplomas in mathematics and environmental science, a MSc in physics and medical physics and a PhD in medical physics.
Jakob has been working with R&D in various contexts since 2001, with a particular interest in mathematical modelling. His major research interest is within radiophysical and radiobiological modelling and analysis of medical images. He is currently affiliated to Örebro University. He is also a research leader at the centre for clinical research and education at Region Värmland.
Jakobs clinical expertise is in the physics of MRI, radiology and nuclear medicine and he is registered as radiation safety expert, approved by the swedish radiation safety authority (SSM).
Jakob has taught primary school, postgraduate and everything in between and is very interested in popularisation of science. His main teaching has been on the subject of Monte Carlo methods and as supervisor of resident physicians as well as bachelor, master and doctoral thesis workers in radiography, engineering physics, medical physics and medical science. He is a regular guest lecturer at Karlstad University.
As an independent consultant, he investigates, educates, measures and calculates within the area of radiation physics for a variety of customers in industry and medicine.
Publications
Articles in journals
- Högberg, J. , Andersén, C. , Rydén, T. & Heydorn Lagerlöf, J. (2024). Comparison of Otsu and an adapted Chan-Vese method to determine thyroid active volume using Monte Carlo generated SPECT images. EJNMMI Physics, 11 (1).
- Krauss, W. , Janusz, F. , Heydorn Lagerlöf, J. , Lidén, M. & Thunberg, P. (2024). Radiomics from multisite MRI and clinical data to predict clinically significant prostate cancer. Acta Radiologica, 23 (1).
- Waldén, M. , Aldrimer, M. , Heydorn Lagerlöf, J. , Eklund, M. , Grönberg, H. , Nordström, T. & Palsdottir, T. (2022). A Head-to-head Comparison of Prostate Cancer Diagnostic Strategies Using the Stockholm3 Test, Magnetic Resonance Imaging, and Swedish National Guidelines: Results from a Prospective Population-based Screening Study. European Urology Open Science, 38, 32-39.
- Andersén, C. , Rydén, T. , Thunberg, P. & H. Lagerlöf, J. (2020). Deep learning based digitisation of prostate brachytherapy needles in ultrasound images. Medical physics, 47 (12), 6414-6420.
- Lagerlöf, J. H. , Rydén, T. & Bernhardt, P. (2018). A Parallel Computation Approach to Detailed 3D Modelling of the Complete Oxygen Distribution in Large Tumours. Cancer Studies and Therapeutics, 3 (4), 1-4.
Conference papers
- Andersén, C. , Rydén, T. , Thunberg, P. & Heydorn Lagerlöf, J. (2019). Presults for the aI-Brachy study: Utilizing deep learning for needle reconstruction in prostate brachytherapy. Paper presented at Nationellt möte om sjukhusfysik 2019, Falkenbergs strandbad, Sverige, 12-15 november, 2019.