A5047320633- Radiomics and Machine Learning in Medical Imaging
- AI in cancer detection
- Medical Image Segmentation Techniques
- Photoacoustic and Ultrasonic Imaging
- COVID-19 diagnosis using AI
- Artificial Intelligence in Healthcare and Education
- Perovskite Materials and Applications
- Solid-state spectroscopy and crystallography
- Infrared Thermography in Medicine
- Chalcogenide Semiconductor Thin Films
- Advanced X-ray and CT Imaging
- Lung Cancer Diagnosis and Treatment
- Advanced Radiotherapy Techniques
- Optical Imaging and Spectroscopy Techniques
University of Oxford
2020-2024
Mirada Medical (United Kingdom)
2021-2024
CRUK/MRC Oxford Institute for Radiation Oncology
2021-2022
Technical University of Munich
2020
Abstract Trap‐related charge‐carrier recombination fundamentally limits the performance of perovskite solar cells and other optoelectronic devices. While improved fabrication passivation techniques have reduced trap densities, properties states their impact on dynamics in metal‐halide perovskites are still under debate. Here, a unified model is presented radiative nonradiative channels mixed formamidinium‐cesium lead iodide perovskite, including trapping, de‐trapping accumulation, as well...
Purpose To investigate a deep learning approach that enables three‐dimensional (3D) segmentation of an arbitrary structure interest given user provided two‐dimensional (2D) contour for context. Such could decrease delineation times and improve contouring consistency, particularly anatomical structures which no automatic tools exist. Methods A series models using Recurrent Residual U‐Net with attention gates was trained successively expanding training set. Contextual information to the...