Principal Investigator: Dr Arne Ewald
Department: Philips GmbH Innovative TechnologiesTags: 51347, artifact reduction, artificial neural networks, biomarker, Machine Learning, neuroimaging, segmentation
Incidences of neurological and psychiatric disorders have largely increased during the last couple of years. However, diagnosis and treatment selection remain difficult and largely depend on the physician. Often the right treatment is determined by a long lasting trial and error phase. Neuroimaging has the potential to assist in early and correct diagnosis and treatment selection. However, there are difficulties in reliable data analysis and processing algorithms, e.g. for segmentation of structural images or in functional data due to image artifacts caused by breathing and motion. During the next three years, we aim to improve these data analysis techniques with modern machine learning approached in order to facilitate scientist and clinicians to improve the lives of millions of individuals suffering from neurological and psychiatric disorders.
Resulting data from our analyses (e.g. fiber-tracts, fMRI networks) will be provided to UK biobank such that they can be used by other researchers. Results will be published in peer-reviewed articles.
Dr Willem Huijbers, Philips Electronics Nederland B.V., Netherlands;
Dr Evan Schwab, Philips Research North America, USA