The objective of this crash course is to introduce and discuss mathematical models for the data formation process in medical imaging and computational methods for the numerical reduction of such models. The syllabus of the course could read as follows:
Overview of medical imaging modalities.
Overview of mathematical models.
Overview of computational methods.
Structural imaging – X-ray tomography.
The Radon Transform and its inversion.
Uniqueness and stability issues.
Filtered Back Projection.
Structural imaging – magnetic resonance imaging.
The signal formation model.
Functional imaging – Parametric imaging.
Tracers and tracer kinetics.
Functional imaging – neurophysiology.
Signal formation models in EEG and MEG.
Artificial intelligence for patients’ stratification.