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Sunil Kumar is a Ph.D. student at Panjab University, India, on a three-month MCnet studentship in Durham. The project was in the collaboration of Durham University and IBEX Innovations Ltd. The aim of the studentship was to develop a biasing method which can be used to reduce the variance of low and high angle Compton scattered events from a pencil beam of X-rays interacting with a sample. The method can be used to provide more accurate scatter kernels at lower computational cost than is achievable using standard GEANT4 methods. A scatter kernel is the point spread function described by the scattering of x-rays from a pencil beam through interaction with a sample. These kernels are used in medical image processing to provide a digital correction of scattering which has been shown to outperform traditional methods of physical scatter rejection using an anti-scatter grid (ASG). To provide an accurate estimate of the scatter, low variance kernels must be generated in GEANT4. Due to the low probability of high angle scatters, the computational cost of producing such kernels is high. This new Compton biasing method has been proven to give both a reduction in variance and a lower computational cost.
Node: 
Durham
Student: 
Sunil Kumar
Date: 
July, 2019 to October, 2019