Biomedical Image Analysis

Biomedical Image Analysis is a research area where new methods and techniques for depicting anatomy and function of the human body and its organs are developed and studied. An important area in this field is the development of non-invasive imaging biomarkers. One example of such biomarkers is fat infiltration in the liver, muscles and other organs.

Earlier, this has commonly been assessed using biopsies, which is often painful and may expose the patient to a risk for complications. By using quantitative magnetic resonance imaging, fat infiltration in various organs can be assessed in a painless and harmless way.

About me

CV

  • MSc, Applied Physics and Electrical Engineering 1991
  • PhD, Computer Vision, 1998
  • Full Professor, 2008 - present
  • Head of the Department of Biomedical Engineering, 2010-2011
  • Associate Dean at the Faculty of Science and Engineering, 2012-2017
  • Founder and CTO, AMRA Medical AB

Field of Teaching

  • I am examiner and lecturer in the course Neural networks and Learning Systems (TBMI26), which is given at many or the Technical faculty's master programs.

Grants (PI)

  • 2020 - 2023: Swedish Research Council, VR/NT: 3,200 kSEK
  • 2016 - 2017: Vinnova: 1,710 kSEK
  • 2016: LiU Cancer: 300 kSEK
  • 2014: LiU Cancer: 150 kSEK
  • 2007-2009: Swedish Research Council, VR/NT, 2,310 kSEK
  • 2006-2008: Swedish Research Council, VR/M, 1,050 kSEK
  • 2003-2005: Swedish Research Council, VR/M, 1,560 kSEK
  • 2003-2005: Vinnova and SSF, 4,000 kSEK

Publications

Selected

Martin E. Lidell, Matthias J. Betz, Olof Dahlqvist Leinhard, Mikael Heglind, Louise Elander, Marc Slawik, Thomas Mussack, Daniel Nilsson, Thobias Romu, Pirjo Nuutila, Kirsi A. Virtanen, Felix Beuschlein, Anders Persson, Magnus Borga, Sven Enerbäck (2013)

Nature Medicine , Vol.19 , s.631-634 Continue to DOI

Latest publications

2023

2022

2021

2020

2019

2018

Research

My research is funded by the Swedish Research Council with the project "Anatomical Manifolds for Interactive Radiomics in Studies of Metabolic and Muscle Degenerative Diseases" (VR: 2019-04751).

Organisation