A5028255958- Advanced Radiotherapy Techniques
- Meningioma and schwannoma management
- Radiation Therapy and Dosimetry
- Nuclear Physics and Applications
- Glioma Diagnosis and Treatment
- Vascular Malformations Diagnosis and Treatment
- Graphite, nuclear technology, radiation studies
- Hand Gesture Recognition Systems
- Advanced X-ray and CT Imaging
- Radioactivity and Radon Measurements
- Advanced Neural Network Applications
- Medical Imaging Techniques and Applications
- Cerebral Venous Sinus Thrombosis
- Bone Tumor Diagnosis and Treatments
- Nuclear reactor physics and engineering
- Lung Cancer Diagnosis and Treatment
- Prostate Cancer Diagnosis and Treatment
- Brain Metastases and Treatment
Queen Square Radiosurgery Centre
2020-2023
American Society for Radiation Oncology
2023
University of California, San Francisco
2022
National Hospital for Neurology and Neurosurgery
2022
University College London
2022
Russian Scientific Center of Radiology and Surgical Technologies
2012-2014
Pontificia Universidad Católica de Chile
2012
Universidad de Sevilla
2012
Hospital Universitario Virgen Macarena
2012
Endesa (Spain)
2012
Automatic segmentation of vestibular schwannomas (VS) from magnetic resonance imaging (MRI) could significantly improve clinical workflow and assist patient management. We have previously developed a novel artificial intelligence framework based on 2.5D convolutional neural network achieving excellent results equivalent to those achieved by an independent human annotator. Here, we provide the first publicly-available annotated dataset VS releasing data annotations used in our prior work....
ABSTRACT Automatic segmentation of vestibular schwannomas (VS) from magnetic resonance imaging (MRI) could significantly improve clinical workflow and assist patient management. We have previously developed a novel artificial intelligence framework based on 2.5D convolutional neural network achieving excellent results equivalent to those achieved by an independent human annotator. Here, we provide the first publicly-available annotated dataset VS releasing data annotations used in our prior...
The Koos grading scale is a frequently used classification system for vestibular schwannoma (VS) that accounts extrameatal tumor dimension and compression of the brain stem. We propose an artificial intelligence (AI) pipeline to fully automate segmentation VS from MRI improve clinical workflow facilitate patient management.We method does not only rely on available images but also automatically generated segmentations. Artificial neural networks were trained tested based manual segmentations...
Knowing the contribution of neutron to collateral effects in treatments is both a complex and mandatory task. This work aims present an operative procedure for estimates any facility using digital detector.The authors' previous established linear relationship between total second cancer risk due neutrons (TR(n)) number MU treatment. Given that detector also presents linearity with MU, its response can be used determine TR(n) per unit denoted as m, normally associated generic Linac model...
Abstract Purpose To compare planning indices achieved using manual and inverse approaches for Gamma Knife radiosurgery of arterio‐venous malformations (AVMs). Methods materials For a series consecutive AVM patients, treatment plans were manually created by expert planners Leksell GammaPlan (LGP). Patients re‐planned new commercially released system, IntuitivePlan. Plan quality metrics calculated both groups compared. Results Overall, IntuitivePlan similar to planners. some plan statistically...
Concerns about the secondary cancer risks associated to peripheral neutron and photon contamination in modern radiotherapy (RT) techniques (e.g., Intensity Modulated RT -IMRT- or Arc Therapy -IMAT) have been widely raised. Benefits terms of better tumor coverage be balanced against drawbacks poorer organ at risk sparing order make decision on optimum treatment technique. The aim this study was develop a tool which estimates success taking into consideration probability.A methodology...