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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

Publications

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) Continue to DOI
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) Continue to DOI
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) Continue to DOI
Iulian Emil Tampu, Tamara Bianchessi, Ida Blystad, Peter Lundberg, Per Nyman, Anders Eklund, Neda Haj-Hosseini (2025) Pediatric brain tumor classification using deep learning on MR-images with age fusion Neuro-Oncology Advances, Vol. 7, Article vdae205 (Article in journal) Continue to DOI

2024

Christoforos Spyretos, Iulian Emil Tampu, Nadieh Khalili, Juan Manuel Pardo Ladino, Per Nyman, Ida Blystad, Anders Eklund, Neda Haj-Hosseini (2024) Early fusion of H&E and IHC histology images for pediatric brain tumor classification Proceedings of Machine Learning Research, p. 192-202 (Conference paper)

Research

Co-Supervisor of Doctoral Students

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

Organisation

News