LMU ART Lab
LMU ART Lab
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Marco Riboldi
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MRgRT real-time target localization using foundation models for contour point tracking and promptable mask refinement
Comparison of deep learning networks for fully automated head and neck tumor delineation on multi-centric PET/CT images
Patient-specific deep learning tracking framework for real-time 2D target localization in MRI-guided radiotherapy
Real-time motion management in MRI-guided radiotherapy: Current status and AI-enabled prospects
Reduction of cone-beam CT artifacts in a robotic CBCT device using saddle trajectories with integrated infrared tracking
Continuous time-resolved estimated synthetic 4D-CTs for dose reconstruction of lung tumor treatments at a 0.35 T MR-linac
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
Head and Neck Cancer Localization with Retina Unet for Automated Segmentation and Time-To-Event Prognosis from PET/CT Images
Intra-frame motion deterioration effects and deep-learning-based compensation in MR-guided radiotherapy
Simultaneous object detection and segmentation for patient-specific markerless lung tumor tracking in simulated radiographs with deep learning
Virtual 4DCT generated from 4DMRI in gated particle therapy: phantom validation and application to lung cancer patients
18F-FET PET radiomics-based survival prediction in glioblastoma patients receiving radio(chemo)therapy
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
DeepClassPathway: Molecular pathway aware classification using explainable deep learning
Offline and online LSTM networks for respiratory motion prediction in MR-guided radiotherapy
Single-isocenter stereotactic radiosurgery for multiple brain metastases: Impact of patient misalignments on target coverage in non-coplanar treatments
Distant metastasis time to event analysis with CNNs in independent head and neck cancer cohorts
Risk Stratification Using 18F-FDG PET/CT and Artificial Neural Networks in Head and Neck Cancer Patients Undergoing Radiotherapy
Porcine lung phantom-based validation of estimated 4D-MRI using orthogonal cine imaging for low-field MR-Linacs
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