Research output per year
Research output per year
Personal profile
Research
My main research focus is on developing and validating deep learning methods for improving and accelerating cardiovascular magnetic resonance (CMR) imaging.
My specific research goals include improving, accelerating, and facilitating CMR during exercise and fetal CMR through deep learning-based automated image analysis methods for motion detection, motion correction, and segmentation.
UKÄ subject classification
- Medical Image Processing
- Computer Vision and Robotics (Autonomous Systems)
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Collaborations the last five years
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Research output
- 5 Article
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Training deep learning based dynamic MR image reconstruction using open-source natural videos
Jaubert, O., Pascale, M., Montalt-Tordera, J., Akesson, J., Virsinskaite, R., Knight, D., Arridge, S., Steeden, J. & Muthurangu, V., 2024 Dec, In: Scientific Reports. 14, 1, 11774.Research output: Contribution to journal › Article › peer-review
Open Access -
Random effects during training: Implications for deep learning-based medical image segmentation
Åkesson, J., Töger, J. & Heiberg, E., 2024 Sept, In: Computers in Biology and Medicine. 180, 108944.Research output: Contribution to journal › Article › peer-review
Open Access -
Diagnostic confidence with quantitative cardiovascular magnetic resonance perfusion mapping increases with increased coverage of the left ventricle
Engblom, H., Ostenfeld, E., Carlsson, M., Åkesson, J., Aletras, A. H., Xue, H., Kellman, P. & Arheden, H., 2024, In: Journal of Cardiovascular Magnetic Resonance. 26, 1, 101007.Research output: Contribution to journal › Article › peer-review
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Deep learning can yield clinically useful right ventricular segmentations faster than fully manual analysis
Åkesson, J., Ostenfeld, E., Carlsson, M., Arheden, H. & Heiberg, E., 2023, In: Scientific Reports. 13, 1, 1216.Research output: Contribution to journal › Article › peer-review
Open Access -
Ventricular longitudinal function by cardiovascular magnetic resonance predicts cardiovascular morbidity in HFrEF patients
Berg, J., Åkesson, J., Jablonowski, R., Solem, K., Heiberg, E., Borgquist, R., Arheden, H. & Carlsson, M., 2022, In: ESC Heart Failure. 9, 4, p. 2313-2324Research output: Contribution to journal › Article › peer-review
Open Access
Projects
- 1 Active
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Deep learning methods for automating and accelerating cardiovascular magnetic resonance imaging
Åkesson, J. (Researcher)
2021/10/01 → …
Project: Dissertation