Motion compensation for multi-modal and multi-parametric preclinical imaging

The current project proposes to study motion correction and cross-platform registration for multi-modal (positron emission tomography (PET), X-ray computed tomography (CT) and magnetic resonance imaging (MRI). Success of this project will significantly improve the resolution and diagnostic value of images. The project will investigate and assess the combined functional imaging capabilities of the aforementioned imaging modalities with experimental data provided by the scanners manufactured by the industrial partner, in the desire to improve the measurement of biological processes at the molecular levels in small animals, and to identify sites of disease within their anatomical reference. In particular, multi-modal registration and motion correction strategies will be investigated in order to derive spatially registered images independent of respiratory and cardiac motion. Such techniques take supplementary and non-redundant information from the MRI, CT and PET data itself or an external monitoring device, such as electro-cardiogram and respiratory tracking system. The student will invert this noisy measurement information using state-of-the-art multi-modal image registration and reconstruction techniques, e.g. the structural joint inversion with regularization, in order to obtain stable and robust solutions and translate them into preclinical and potentially clinical practice.