16 results on '"Lasnon, Charline"'
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2. Artificial intelligence-based PET denoising could allow a two-fold reduction in [18F]FDG PET acquisition time in digital PET/CT
3. The impact of introducing deep learning based [18F]FDG PET denoising on EORTC and PERCIST therapeutic response assessments in digital PET/CT.
4. HYPHYCA: a prospective study in 613 patients conducting a comprehensive analysis for predictive factors of physiological 18F-FDG anal uptake
5. Assessment of alteration in liver 18F–FDG uptake due to steatosis in lymphoma patients and its impact on the Deauville score
6. Diagnostic and prognostic value of baseline FDG PET/CT skeletal textural features in diffuse large B cell lymphoma
7. Impact of the EARL harmonization program on automatic delineation of metabolic active tumour volumes (MATVs)
8. EORTC PET response criteria are more influenced by reconstruction inconsistencies than PERCIST but both benefit from the EARL harmonization program
9. Deep Learning Denoising Improves and Homogenizes Patient [ 18 F]FDG PET Image Quality in Digital PET/CT.
10. Patient’s weight: a neglected cause of variability in SUV measurements? A survey from an EARL accredited PET centre in 513 patients
11. Prediction of the Presence of Targetable Molecular Alteration(s) with Clinico-Metabolic 18 F-FDG PET Radiomics in Non-Asian Lung Adenocarcinoma Patients.
12. Artificial intelligence-based PET denoising could allow a two-fold reduction in [18F]FDG PET acquisition time in digital PET/CT.
13. Harmonizing SUVs in multicentre trials when using different generation PET systems: prospective validation in non-small cell lung cancer patients
14. End-of-treatment 18F-FDG PET/CT in diffuse large B cell lymphoma patients: ΔSUV outperforms Deauville score.
15. Assessment of alteration in liver 18F-FDG uptake due to steatosis in lymphoma patients and its impact on the Deauville score.
16. How fast can we scan patients with modern (digital) PET/CT systems?
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