Forskningsoutput per år
Forskningsoutput per år
Personlig profil
Forskning
My main research focus is on developing deep learning methods for improving and accelerating cardiovascular magnetic resonance (CMR) imaging.
My specific research goals include improving, accelerating, and facilitating new CMR methods, including exercise CMR, through deep learning-based methods for motion detection, segmentation, and reconstruction. My research goals also include the development of new MRI pulse sequences.
Ämnesklassifikation (UKÄ)
- Medicinsk bildvetenskap
- Datorgrafik och datorseende
Fria nyckelord
- Deep learning
- Magnetic Resonance Imaging
- Image analysis
- Image processing
Fingeravtryck
Utforska forskningsämnen där Julius Åkesson är aktiv. Dessa ämnesetiketter kommer från personens arbeten. Tillsammans bildar de ett unikt fingeravtryck.
- 1 Liknande profiler
Samarbeten under de senaste fem åren
Externa samarbeten med länder/områden de senaste 5 åren
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Atrioventricular Area Difference Assessed by Exercise Cardiovascular Magnetic Resonance Shows Impaired Diastolic Filling in Heart Failure Patients
Edlund, J., Östenson, B., Åkesson, J., Heiberg, E., Arheden, H. & Steding-Ehrenborg, K., 2026 jan. 27, (E-pub ahead of print) I: Journal of Applied Physiology.Forskningsoutput: Tidskriftsbidrag › Artikel i vetenskaplig tidskrift › Peer review
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On Deep Learning in Cardiovascular Magnetic Resonance Imaging
Åkesson, J., 2025 sep. 22, Lund: Department of Biomedical Engineering, Lund university. 171 s.Forskningsoutput: Avhandling › Doktorsavhandling (sammanläggning)
Öppen tillgångFil58 Nedladdningar (Pure) -
Retrospectively synchronized time-resolved ventricular cine images from 2D real-time exercise cardiac magnetic resonance imaging
Åkesson, J., Edlund, J., Steding-Ehrenborg, K. & Heiberg, E., 2025 sep., I: Clinical Physiology and Functional Imaging. 45, 5, e70027.Forskningsoutput: Tidskriftsbidrag › Artikel i vetenskaplig tidskrift › Peer review
Öppen tillgång -
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., I: Scientific Reports. 14, 1, 11774.Forskningsoutput: Tidskriftsbidrag › Artikel i vetenskaplig tidskrift › Peer review
Öppen tillgång -
Random effects during training: Implications for deep learning-based medical image segmentation
Åkesson, J., Töger, J. & Heiberg, E., 2024 sep., I: Computers in Biology and Medicine. 180, 108944.Forskningsoutput: Tidskriftsbidrag › Artikel i vetenskaplig tidskrift › Peer review
Öppen tillgång
Projekt
- 1 Aktiva
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Deep learning methods for automating and accelerating cardiovascular magnetic resonance imaging
Åkesson, J. (Forskare)
2021/10/01 → …
Projekt: Avhandling