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Ida Blystad

Adjunct Associate Professor, Docent

My research is grounded in neuroradiology with focus on imaging of the brain in multidisciplinary projects.

Presentation

My research is grounded in neuroradiology with a focus on imaging of the brain in multidisciplinary projects. Using different techniques, such as magnetic resonance imaging and computed tomography, we investigate different pathological conditions of the brain in an adult and pediatric population. Some research areas covered are brain tumors and fatigue.

Publications

2025

Richard Levi, Ulrika Birberg Thornberg, Ida Blystad, Anestis Divanoglou, David Engblom, Felipe Leon, Sofia Morberg Jämterud, Kristin Zeiler (2025) Reconceptualizing rehabilitation research via an enactive framework and a radically interdisciplinary cross-analysis: a study protocol on fatigue in post COVID-19 condition (PCC) Journal of Rehabilitation Medicine, Vol. 57, p. jrm42254-jrm42254 (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)
Christian Jamtheim Gustafsson, Tommy Löfstedt, Mattias Åkesson, Viktor Rogowski, Muhammad Usman Akbar, Andreas Hellander, Peter Larsson, Annika Malmström, Ida Blystad, Anders Eklund (2024) Federated training of segmentation models for radiation therapy treatment planning Radiotherapy and Oncology, Vol. 194, p. S4819-S4822 (Article in journal) 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, Article 259 (Article in journal) Continue to DOI

Research

Organisation

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