In dynamic magnetic resonance imaging (MRI) studies, the motion kinetics or the contrast variability are often hard to predict, hampering an appropriate choice of the image update rate or the temporal resolution. A constant azimuthal profile spacing (111.246 degrees), based on the Golden Ratio, is investigated as optimal for image reconstruction from an arbitrary number of profiles in radial MRI. The profile order is evaluated and compared with a uniform profile distribution in terms of signal-to-noise ratio (SNR) and artifact level. The favorable characteristics of such a profile order are exemplified in two applications on healthy volunteers. First, an advanced sliding window reconstruction scheme is applied to dynamic cardiac imaging, with a reconstruction window that can be flexibly adjusted according to the extent of cardiac motion that is acceptable. Second, a contrast-enhancing k-space filter is presented that permits reconstructing an arbitrary number of images at arbitrary time points from one raw data set. The filter was utilized to depict the T1-relaxation in the brain after a single inversion prepulse. While a uniform profile distribution with a constant angle increment is optimal for a fixed and predetermined number of profiles, a profile distribution based on the Golden Ratio proved to be an appropriate solution for an arbitrary number of profiles.
Conference Contributions (2)
T. Baas, H. Köhler, H. Malberg, and O. Dössel. Automatic blood pressure segmentation algorithm for analysing morphology changes. In Biomedizinische Technik / Biomedical Engineering (Proceedings BMT2010), vol. 55(1) , pp. 168-171, 2010
Simultaneous recording of ECG, Atrial Blood Pressure (ABP) and respiration is possible and sometimes done to investigate cardiovascular and respiration coupling. But analysis most often concentrates on Heart Rate Variability (HRV) and Blood Pressure Variability (BPV). Although analysis of HRV and BPV has lead to important clinical information in the past, an investigation of the morphology of the time course of ECG and ABP could reveal additional diagnostic information.To analyse the morphology of the Blood Bressure (PB) wave a detection of characteristic points, outliers and boundaries is necessary. A wavelet based algorithm for blood pressure segmentation with outlier detection is presented in this paper. It is tested on 108 records with durations of 30 minutes each.
H. Köhler. Entwicklung eines multivariaten autoregressiven Modells zur Identifizierung von Myokarditis Erkrankungen. Institut für Biomedizinische Technik, Karlsruher Institut für Technologie (KIT). Diplomarbeit. 2010