about ESR(13) Michael Trimpl

PhD student at Mirada Medical

Radiomics and Machine Learning based segmentation of tumours.

Michael was a DPhil Candidate at the University of Oxford. His research focused on interactive machine learning tools in medical image segmentation for radiotherapy planning. He studied physics in his BSc and MSc at the Technical University of Munich, the National University of Singapore, the Pontifica Universidad Catolica de Chile and the University of Oxford. In his PhD project Michael will focus on Radiomics and Machine Learning based segmentation of tumours. 

Mirada Medical has developed several semi-automated algorithms for the segmentation of lesions in CT and MRI images. These have been validated for volumetric segmentation of well-defined lesions where the user is expected to use the tool in an interactive manner. These tools do not function well where the lesions exhibit an unclear boundary on the image and moreover are not automated. This project has two primary objectives: 1) to develop novel techniques using Radiomics and Machine Learning methods to provide fully automated tumour segmentation techniques, 2) to develop segmentation methods that work across the wide range of real tumour types that are of focus in this consortium, in particular lung, liver and head & neck. The technical work can take place at Mirada and the secondments will be used to integrate the methods into the Radiomics platform in WP1 and to validate the methods in clinical sites.