Defence of doctoral thesis in the field of biomedical engineering, MSc (Tech) Antti Mäkinen
Title of the doctoral thesis is "Applications of magnetic-field modeling for hybrid MEG and MRI"
The brain has been studied via magnetic phenomena for decades. Information about the structure of the brain can be obtained by magnetic resonance imaging (MRI). To infer how the brain works, the magnetic field generated by its electrical activity can be recorded by the means of magnetoencephalography (MEG). At Aalto University, these two conventionally incompatible brain imaging methods have been merged in a single hybrid MEG–MRI device. The hybrid imaging enables new ways of studying brain disorders and facilitates the execution of functional brain imaging experiments.
To achieve higher spatial accuracies in the imaging, the spatial characteristics of the magnetic fields must be known and modeled correctly. In this Thesis, computational methods were developed to model and utilize the magnetic fields present in the imaging. For instance, accurate field modeling was used to develop a method to spatially calibrate MEG and MRI so that they can automatically be handled in the same coordinate system. Furthermore, an open-source software for magnetic-field modeling was created with the aim of facilitating the design and analysis of the fields used in the imaging. Besides the hybrid imaging, the methods developed in this Thesis can be used in other application areas that deal with low-frequency magnetic fields.
Opponent: Professor Matthew Rosen, Harvard Medical School; MGH/Martinos Center for Biomedical Imaging, Boston, Massachusetts, USA
Custos: Professor Risto Ilmoniemi, Aalto University School of Science, Department of Neuroscience and Biomedical Engineering
Contact information of the doctoral candidate: Antti Mäkinen, Neurotieteen ja lääketieteellisen tekniikan laitos,
p. 0445713188, [email protected]
The defence will be organised via remote technology (Zoom). Link to the defence.
Zoom Quick Guide (www.aalto.fi)
The doctoral thesis will be publicly displayed 10 days before the defence on the publication archive of Aalto University (aaltodoc.aalto.fi).
Electronic dissertation (aaltodoc.aalto.fi)