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Anders Eklund

Senior Associate Professor

I am an associate professor and share my time between the Department of Biomedical Engineering (IMT) and the Department of Computer and Information Science (IDA).

Development of new methods for medical images

My research is about analyzing medical images and developing new methods (image processing, statistics, machine learning) for extracting important information from the images.

     
     
     
     

About me

CV

  • 2007 Master of Science, applied physics & electrical engineering 
  • 2012 PhD, medical informatics
  • 2012-2014 Postdoc, Virginia Tech
  • 2016 Docent, medical informatics
  • 2021 Associate Professor

Field of teaching

I teach the following courses: 

Publications

2023

Johan Jönemo, Anders Eklund (2023) Brain Age Prediction Using 2D Projections Based on Higher-Order Statistical Moments and Eigenslices from 3D Magnetic Resonance Imaging Volumes Journal of Imaging, Vol. 9, p. 271-271 Continue to DOI
Deneb Boito, Anders Eklund, Anders Tisell, Richard Levi, Evren Özarslan, Ida Blystad (2023) MRI with generalized diffusion encoding reveals damaged white matter in patients previously hospitalized for COVID-19 and with persisting symptoms at follow-up Brain Communications, Vol. 5, Article fcad284 Continue to DOI
Jörg Schilcher, Alva Nilsson, Oliver Andlid, Anders Eklund (2023) Fusion of electronic health records and radiographic images for a multimodal deep learning prediction model of atypical femur fractures Computers in Biology and Medicine, Vol. 168, Article 107704 Continue to DOI
Christoforos Spyretos, Iulian Emil Tampu, Anders Eklund, Neda Haj-Hosseini (2023) Classification of Brain Tumour Tissue in Histopathology Images Using Deep Learning
Johan Jönemo, Muhammad Usman Akbar, Robin Kämpe, J. Paul Hamilton, Anders Eklund (2023) Efficient Brain Age Prediction from 3D MRI Volumes Using 2D Projections Brain Sciences, Vol. 13, Article 1329 Continue to DOI

Publications in Google Scholar

Publications in DiVA

Research

Image: Anders Brun, Hae-Jeong Park, Hans Knutsson och Carl-Fredrik Westin

Biomedical Image Science

We develop methods & techniques for depicting anatomy & function in the human body & its organs. From imaging techniques, through methods of analysis and quantification of image information, to validation of new methods and image-based biomarkers
MRI photo of a human head.

ASSIST

In this VINNOVA/ITEA project, the goal is to streamline radiation therapy for the treatment of tumours. In this project, IMT collaborates with RaySearch, Spectronic, Inovia and Eigenvision.
fMRI tumour

Bayesian fMRI tumour

In this CENIIT project, Bayesian methods for fMRI informed brain tumour treatment planning, the goal is to improve treatment of brain tumours, by including images of brain activity in Elektas software for tumour treatment planning.

Supervisor of Doctoral Students

Johan Jönemo

PhD student

Co-Supervisor of Doctoral Students

Photo of Josef Wilzén

Josef Wilzén

Lecturer

Photo of Robin Kämpe

Robin Kämpe

Research Engineer

Photo of Christoforos Spyretos

Christoforos Spyretos

PhD student

Mats Svantesson
Photo of Iulian Emil Tampu

Iulian Emil Tampu

PhD student

PhD Graduates (Co-Supervisor)

Olivier Cros, 2017

Jens Sjölund, 2018

Per Sidén, 2020

PhD Graduates (Main Supervisor)

Xuan Gu, 2019

Marco Domenico Cirillo, 2021

David Abramian, 2023

Organisation

Institutionen för medicinsk teknik

Department of Biomedical Engineering (IMT)

A national centre for research, PhD studies and graduate studies within biomedical engineering, since 1972.
Image of Building E, Campus Valla.

Department of Computer and Information Science (IDA)

The Department of Computer and Information Science is one of the largest departments in northern Europe in its field. Research activity covers artificial intelligence, human-computer interaction, software and computer systems, and data science.
Two scientists are sitting infront of an MRI

Center for Medical Image Science and Visualization (CMIV)

CMIV conducts focused front-line research providing solutions to tomorrow’s clinical issues. The CMIV mission is to develop future methods and tools for image analysis and visualization for applications within health care and medical research.

News

A MRI photo of a human brain with a brain tumour.

Reducing healthcare queues after the pandemic

At the end of September, the ASSIST project received 9 million sek in funding. The hope is that their research on automated analysis of brain images will be able to free up time for healthcare professionals.
Anders Eklund

Softwares for fMRI yield erroneous results

Common statistical methods used to analyse brain activity through images taken with MRI scanners cannot be trusted, as shown by Anders Eklund and Hans Knutsson of Linköping University, in the highly-ranked journal PNAS.

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