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

Selected publications

Jörg Schilcher, Alva Nilsson, Oliver Andlid, Anders Eklund (2024)

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 Continue to DOI

Muhammad Usman Akbar, Måns Larsson, Ida Blystad, Anders Eklund (2024)

Brain tumor segmentation using synthetic MR images - A comparison of GANs and diffusion models

Scientific Data , Vol.11 Continue to DOI

Anders Eklund, Thomas Nichols, Hans Knutsson (2016)

Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates

Proceedings of the National Academy of Sciences of the United States of America , Vol.113 , s.7900-7905 Continue to DOI

Latest publications

2026

Anders Eklund (2026)

Increasing statistical power in functional MRI through permutation and multivariate statistics Cognitive Neuroscience, p. 1-2 (Article in journal)

https://dx.doi.org/10.1080/17588928.2026.2682170

Kristin Zeiler, Sofia Morberg Jämterud, F. León, Agnes Andersson, Ulrika Birberg Thornberg, Ida Blystad, Anestis Divanoglou, Anders Eklund, David Engblom, Richard Levi (2026)

Affective dimensions of fatigue in post COVID-19 condition: An interdisciplinary investigation across phenomenology and biomedicine Phenomenology and the Cognitive Sciences (Article in journal)

https://dx.doi.org/10.1007/s11097-026-10151-5

2025

Alfredo Ordinola, David Abramian, Magnus Herberthson, Anders Eklund, Evren Özarslan (2025)

Super-resolution mapping of anisotropic tissue structure with diffusion MRI and deep learning Scientific Reports, Vol. 15, Article 6580 (Article in journal)

https://dx.doi.org/10.1038/s41598-025-90972-7

Humaira Batool, Asmat Mukhtar, Sajid Gul Khawaja, Norah Saleh Alghamdi, Asad Mansoor Khan, Adil Qayyum, Ruqqayia Adil, Zawar Khan, Muhammad Usman Akram, Muhammad Usman Akbar, Anders Eklund (2025)

Knowledge Distillation and Transformer Based Framework for Automatic Spine CT Report Generation IEEE Access, p. 1-1 (Article in journal)

https://dx.doi.org/10.1109/access.2025.3546131

Muhammad Usman Akbar, Wuhao Wang, Anders Eklund (2025)

Beware of diffusion models for synthesizing medical images - A comparison with GANs in terms of memorizing brain MRI and chest x-ray images Machine Learning: Science and Technology (Article in journal)

https://dx.doi.org/10.1088/2632-2153/ad9a3a

Publications in Google Scholar

Publications in DiVA

Research

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.

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.

Co-Supervisor of Doctoral Students

Josef Wilzén

Lecturer

Robin Kämpe

Research Engineer

Christoforos Spyretos

PhD student

PhD Graduates (Co-Supervisor)

Olivier Cros, 2017

Jens Sjölund, 2018

Per Sidén, 2020

Deneb Boito, 2024

Mats Svantesson, 2024

Iulian Emil Tampu, 2024

PhD Graduates (Main Supervisor)

Xuan Gu, 2019

Marco Domenico Cirillo, 2021

David Abramian, 2023

Johan Jönemo (licentiate degree), 2024

News

The image consists of two parts: four sections views of a brain on the one side and fous sections of another brain on the other side

26 April 2024

Synthetic images can save a lot of time in healthcare

AI makes it possible to quickly and accurately mark areas to be eliminated with radiation when treating cancerous tumors. But due to lack of medical data to train AI models with, attempts are underway to train models with synthetic medical images.

Info graphics with illustrations showing how local updates are being sent from the hospitals to a cloud. The cloud sends a new global modell to the hospitals. The trained model gives personal healthcare.

16 April 2024

Developing medical AI without sharing sensitive information

Sharing sensitive data, such as images of brain tumor patients, is complicated. This makes development of AI models for medical image analysis challenging. LiU researchers shows how such models can be trained without sharing sensitive information.

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

03 November 2021

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.

Organisation

A monitor displaying health data for a patient.

Division of Biomedical Engineering (MT)

A division for research, education and innovation within the field of biomedical engineering.

Department of Biomedical Engineering (IMT)

A national centre for research, PhD studies and graduate studies within biomedical engineering, since 1972.

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.