Modelling X-Ray photon transport through a transformer-based neural network in computed tomography forward projection

Radiotherapy is one of the main treatments for cancer and relies heavily on CT images to calculate radiation dose. With research on radiotherapy moving to adaptive treatments aiming to calculate these doses at real-time speeds while maintaining high precision, a need for accurate CT imaging at comparable real-time speeds has emerged. Currently,...

Assessing the applicability of Transformer-based architectures as rainfall-runoff models

Modeling the relationship between rainfall and runoff is a longstanding challenge in hydrology and is crucial for informed water management decisions. Recently, Deep Learning models, particularly Long short-term memory (LSTM), have shown promising results in simulating this relationship. The Transformer, a newly proposed deep learning...

VideoMuscle: Estimating human musculoskeletal model using neural networks from monocular video

We present the first deep learning approach to estimate the human skeletal system of the musculoskeletal model from monocular video. The current practice of musculoskeletal modeling relies on a motion capture system and OpenSim. The data is recorded in a restricted environment, and OpenSim workflow for musculoskeletal modeling is costly. Our...

Proton Therapy Dose Calculations Using A Transformer Deep Learning Algorithm

Proton therapy is a great way to treat cancer, since protons can concentrate energy on one single spot, which minimises the irradiated healthy tissue. Because of this property protons are sensitive to uncertainties. Since the tumour is not stationary throughout the treatment, multiple scans are essential. With the current dose calculation...