Nuclear medicine, Malmö
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- 2021
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Mark
Head-to-head comparison of a Si-photomultiplier-based and a conventional photomultiplier-based PET-CT system
(
- Contribution to journal › Article
- 2020
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Mark
Deep learning-based quantification of PET/CT prostate gland uptake : association with overall survival
(
- Contribution to journal › Article
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Mark
Auto-segmentations by convolutional neural network in cervical and anorectal cancer with clinical structure sets as the ground truth
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- Contribution to journal › Article
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Mark
Optimization of [18F]PSMA-1007 PET-CT using regularized reconstruction in patients with prostate cancer
(
- Contribution to journal › Article
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Mark
Evaluation of 18F-FDG uptake in lung parenchyma compensating for tissue fraction : Comparison between non-enhanced low dose CT and intravenous contrast-enhanced diagnostic CT
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- Contribution to journal › Article
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Mark
Denoising of Scintillation Camera Images Using a Deep Convolutional Neural Network : A Monte Carlo Simulation Approach
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- Contribution to journal › Article
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Mark
Artificial intelligence in PET-CT. From Image Enhancement to Imaging Biomarkers.
2020) In Lund University, Faculty of Medicine Doctoral Dissertation Series(
- Thesis › Doctoral thesis (compilation)
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Mark
RECOMIA—a cloud-based platform for artificial intelligence research in nuclear medicine and radiology
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- Contribution to journal › Article
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Mark
Deep learning-based evaluation of normal bone marrow activity in 18F-NaF PET/CT in patients with prostate cancer
(
- Contribution to journal › Published meeting abstract
- 2019
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Mark
Impact of penalizing factor in a block-sequential regularized expectation maximization reconstruction algorithm for
18
F-fluorocholine PET-CT regarding image quality and interpretation
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- Contribution to journal › Article