A5021068316- Advanced X-ray and CT Imaging
- Medical Imaging Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
- Radiation Dose and Imaging
- Particle physics theoretical and experimental studies
- Advanced X-ray Imaging Techniques
- Meningioma and schwannoma management
- Particle Detector Development and Performance
- Ultrasound in Clinical Applications
- Glioma Diagnosis and Treatment
- Advanced Radiotherapy Techniques
- Radiation Detection and Scintillator Technologies
- Atomic and Subatomic Physics Research
- Vascular Malformations Diagnosis and Treatment
- Lung Cancer Diagnosis and Treatment
Royal Marsden NHS Foundation Trust
2021-2024
Institute of Cancer Research
2023-2024
Technical University of Munich
2021-2023
Imperial College London
2022-2023
Max Planck Institute for Physics
2016
To compare the visibility of anatomical structures and overall quality attenuation images obtained with a dark-field X-ray radiography prototype those from commercial system.Each 65 patients recruited for this study thorax radiograph at reference system. Five radiologists independently assessed structures, level motion artifacts, image all on five-point scale, 5 points being highest rating. The average scores were compared between two types. differences evaluated using an area under curve...
The SuperKEKB collider at KEK, which has started its commissioning with beam in February 2016, is designed to achieve unprecedented luminosities, a factor 40 higher than the record-breaking luminosity of KEKB machine. For operation Belle II detector, particular pixel vertex precise understanding background conditions interaction point accelerator crucial. To study these prior final installation experiment, dedicated detector setup consisting different subsystems been installed for first...
Automatic segmentation of tumour volumes for stereotactic radiosurgery (SRS) treatment planning could reduce uncertainties introduced by time-consuming and operator-dependent manual delineation. Previous works have shown high performance machine learning deep approaches to tackle this problem. This study investigates the two existing frameworks vestibular schwannoma (VS), a benign nerve clinical indication SRS. The convolutional neural network DeepMedic is trained tested on publicly...
The current stereotactic radiosurgery treatment planning pipeline involves manual delineation of tumour volumes and the registration MRI conventional CT scan patient, leading to uncertainties in workflow. We propose alleviate these by introducing photon-counting as a single imaging modality combination with deep-learning based segmentation. developed an simulate reconstruct images brain. Additionally, we trained tested deep learning model DeepMedic on data glioma patients. observe low...
Treatment planning for stereotactic radiosurgery is based on manual delineation of tumour volumes and image registration the CT MRI patient scan, which can lead to uncertainties in clinical workflow. These could be alleviated by implementing deep learning-based contouring a single modality imaging technique. This study investigates performance learning models DeepMedic nnU-Net automatic segmentation two different data sets. In first experiment, both are trained vestibular schwannoma...
Einführung: Eine Röntgenaufnahme wird häufig für die initiale Untersuchung oder zur Verlaufsbeurteilung des Thorax angewandt. Die Erkennung von strukturellen Schäden, insbesondere bei frühen Formen, ist jedoch begrenzt. Dunkelfeldtechnik (X-ray dark-field imaging, XDF) ermöglich Erfassung kohärenter Kleinwinkelstreuung, wodurch Dichtefluktuationen wie z. B. an den Alveolarmembranen sichtbar werden. Durch diese Studie sollen ersten Eindrücke mit dieser neuen Technik vorgestellt