Improving Signal Prediction of a Real-time Radiotherapy Beam Monitor using Artificial Neural Network

The science and technology of Radiotherapy for treating cancerous tumor more accurately and precisely is improving constantly with the availability of cutting-edge imaging systems in Radiation Treatment room, and advancements in computer technologies. However, these improvements are associated with complexities and potential risks. To mitigate the risks, a new class of Quality Assurance (QA) systems are emerging. In this research project, the student will investigate further enhancements in the performance of a recently commercialized QA system (IQM system) by incorporating a Machine Learning method. It is expected that an Improved IQM system can be an enabler for clinical deployment of advanced Radiotherapy techniques, and consequently our industry partner will benefit from the improvements in the customer demands of the IQM system.

Faculty Supervisor:

Mohammad Islam

Student:

Susanne Tiraei

Partner:

iRT Systems GmbH

Discipline:

Engineering - biomedical

Sector:

Medical devices

University:

Program: