Diagnostic Radiology, (Lund)
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- 2025
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Mark
Advanced Imaging in the Diagnosis and Response Assessment of High-Grade Glioma : AJR Expert Panel Narrative Review.
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- Contribution to journal › Scientific review
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Mark
ESR Essentials : basic physics of MR safety—practice recommendations by the European Society for Magnetic Resonance in Medicine and Biology
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- Contribution to journal › Scientific review
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Mark
Left Ventricular Diastolic Function in Children with Atrial Septal Defects Improves After Closure by Means of Increased Hydraulic Force.
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- Contribution to journal › Article
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Mark
NeuroNCAP : Photorealistic Closed-Loop Safety Testing for Autonomous Driving
2025) 18th European Conference on Computer Vision, ECCV 2024 In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 15088 LNCS. p.161-177(
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
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Mark
SONNET : Enhancing Time Delay Estimation by Leveraging Simulated Audio
2025) 27th International Conference on Pattern Recognition, ICPR 2024 In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 15320 LNCS. p.289-303(
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
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Mark
Dual-layer detector dual energy CT applications for neuroradiology - Spectral brain imaging
2025) In Lund University, Faculty of Medicine Doctoral Dissertation Series(
- Thesis › Doctoral thesis (compilation)
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Mark
The Nutmeg Lung Pattern in a Fetus with Hypoplastic Left Heart Syndrome and Turner Syndrome
2025) In Pediatric Cardiology(
- Contribution to journal › Article
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Mark
Differentiation between glioblastoma and solitary brain metastases using perfusion and amide proton transfer weighted MRI
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- Contribution to journal › Article
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Mark
A multi-cohort study of longitudinal and cross-sectional Alzheimer's disease biomarkers in cognitively unimpaired older adults
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- Contribution to journal › Article
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Mark
Outcome prediction of prostate cancer patients on active surveillance using weakly supervised deep learning
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- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding