Stefanie Corradini

Latest

• Repeatability quantification of brain diffusion-weighted imaging for future clinical implementation at a low-field MR-linac
• Auto-segmentation of pelvic organs at risk on 0.35T MRI using 2D and 3D Generative Adversarial Network models
• CloverNet -- Leveraging Planning Annotations for Enhanced Procedural MR Segmentation: An Application to Adaptive Radiation Therapy
• Impact of daily plan adaptation on accumulated doses in ultra-hypofractionated magnetic resonance-guided radiation therapy of prostate cancer
• MRI-based ventilation and perfusion imaging to predict radiation-induced pneumonitis in lung tumor patients at a 0.35T MR-Linac
• Patient-specific deep learning tracking framework for real-time 2D target localization in MRI-guided radiotherapy
• Proton dose calculation with LSTM networks in presence of a magnetic field
• Reduction of cone-beam CT artifacts in a robotic CBCT device using saddle trajectories with integrated infrared tracking
• The role of online MR-guided multi-fraction stereotactic ablative radiotherapy in lung tumours
• Pulmonary magnetic resonance-guided online adaptive radiotherapy of locally advanced: the PUMA trial
• Deep learning based automatic segmentation of organs-at-risk for 0.35 T MRgRT of lung tumors
• Evaluation of real-time tumor contour prediction using LSTM networks for MR-guided radiotherapy
• Experimental comparison of linear regression and LSTM motion prediction models for MLC-tracking on an MRI-linac
• Prior knowledge based deep learning auto-segmentation in magnetic resonance imaging-guided radiotherapy of prostate cancer
• Simultaneous object detection and segmentation for patient-specific markerless lung tumor tracking in simulated radiographs with deep learning
• Ventilation and perfusion MRI at a 0.35 T MR-Linac: feasibility and reproducibility study
• 18F-FET PET radiomics-based survival prediction in glioblastoma patients receiving radio(chemo)therapy
• Dosimetric benefit of MR-guided online adaptive radiotherapy in different tumor entities: liver, lung, abdominal lymph nodes, pancreas and prostate
• Assessment of intrafractional prostate motion and its dosimetric impact in MRI-guided online adaptive radiotherapy with gating
• Deep learning based time-to-event analysis with PET, CT and joint PET/CT for head and neck cancer prognosis
• Evaluation of an anthropomorphic ion chamber and 3D gel dosimetry head phantom at a 0.35 T MR-linac using separate 1.5 T MR-scanners for gel readout
• ExacTrac Dynamic workflow evaluation: Combined surface optical/thermal imaging and X-ray positioning
• Intrafractional monitoring of patients using four different immobilization mask systems for cranial radiotherapy
• MR-guided SBRT boost for patients with locally advanced or recurrent gynecological cancers ineligible for brachytherapy: feasibility and early clinical experience
• Offline and online LSTM networks for respiratory motion prediction in MR-guided radiotherapy
• Dosimetric comparison of MR-linac-based IMRT and conventional VMAT treatment plans for prostate cancer
• Comparison of liver exposure in CT-guided high-dose rate (HDR) interstitial brachytherapy versus SBRT in hepatocellular carcinoma
• Distant metastasis time to event analysis with CNNs in independent head and neck cancer cohorts
• Feasibility and Early Clinical Experience of Online Adaptive MR-Guided Radiotherapy of Liver Tumors
• Risk Stratification Using 18F-FDG PET/CT and Artificial Neural Networks in Head and Neck Cancer Patients Undergoing Radiotherapy
• Validation of the collapsed cone algorithm for HDR liver brachytherapy against Monte Carlo simulations
• Radiotherapy in oncological emergencies: fast-track treatment planning
• The dosimetric impact of replacing the TG-43 algorithm by model based dose calculation for liver brachytherapy