Speaker
Description
In this talk, we will present the application of machine learning techniques to address many medical physics problems such as positron range correction in PET, dose estimation in radiotherapy planning, the guidance of ultrasound acquisitions, tissue segmentation, automatic lesion detection… We will focus on the risks and potential benefits of these new techniques compared to current standard methods. A summary of the most common challenges in the implementation of these techniques and how to overcome them will be also presented. In conclusion, machine learning tools have the potential to revolutionize all the areas of physics, providing solutions beyond what is currently possible, and being so new, it is a great field for young researchers.
