Speaker
Kamila Kalecińska
(AGH University of Science and Technology)
Description
Big variety of medical data types and their complex structure may be a challenge for data scientists. The process of creating the data is usually time-consuming, while access to medical facilities databases is limited due to privacy issues.
Generative models can be of great help in the process of data augmentation. The presentation will contain the idea, current status and results of generative models training (AutoEncoders, GANs) in order to build a tool for generating medical data: 3D medical DICOM images representing the patient's geometry as well as phase space files necessary in the process of simulating the radiotherapy dose deposited in the phantom.
Primary authors
Kamila Kalecińska
(AGH University of Science and Technology)
consortium Dose-3D
