Mathematical Fits to Enhance Temporal Accuracy in Event Detection in Quantitative Fluorescence Angiography
In neurovascular surgery the surgeon tries to restore the vascular function, in particular the blood flow (ml/s). State of the Art methods rely on tissue contact or even wrap around the vessel which is increasing the risk of complications while intervention. Optical methods could encounter this risk and provide the surgeon with curial information. Quantitative fluorescence angiography is a research focus in the institute. Hereby a camera is integrated into the microscope and records the fluorescence dynamic of Indocyanine Green (ICG) in the NIR. Its temporal resolution is limited (~30fps) but a precise determination of the transit time is need. Therefore mathematical/physiological models can be fitted onto data to compute a sub-framerate temporal resolution. In this thesis the ground truth is derived from in silico simulation in COMSOL and exported to fit mathematical models in MATLAB and evaluate their performance in terms of increased temporal precision.
The project consists of a literature research on indicator dilution theory, mathematical fits and obtaining sub-framerate precision. The implementation is done in COMSOL and MATLAB.