Super-resolution reconstruction (SRR) algorithms are used for getting high-resolution (HR) data from low-resolution
observations. In Maximum a posteriori (MAP) based SRR the observation model is employed for
estimating a HR image that best reproduces the two low-resolution input data sets. The parameters of the
prior play a significant role in the MAP based SRR. This work concentrates on the investigation of the influence
of one such parameter, called temperature, on the reconstructed 3D MR images. The existing approaches on
SRR in 3D MR images use a constant value for this parameter. We use a cooling schedule similar to simulated
annealing for computing the value of the temperature parameter at each iteration of the SRR. We have used
3D MR cardiac data sets in our experiments and have shown that the iterative computation of the temperature
which resembles simulated annealing delivers better results.
Selecting the best catheter prior to coronary angiography significantly reduces the exposure time to radiation
as well as the risk of artery punctures and internal bleeding. In this paper we describe a simulation based
technique for selecting an optimal catheter for right coronary angiography using the Simulation Open Framework
Architecture (SOFA). We simulate different catheters in a patient-specific arteries model, obtain final placement
of different catheters and suggest an optimally placed catheter. The patient-specific arteries model is computed
from the patient image data acquired prior to the intervention and the catheters are modeled using Finite Element
During coronary artery angiography, a catheter is used to inject a contrast dye into the coronary arteries. Due
to the anatomical variation of the aorta and the coronary arteries in different humans, one common catheter
cannot be used for all patients. The cardiologists test different catheters for a patient and select the best catheter
according to the patient's anatomy. This procedure is time consuming and there is a slight chance of cancer from
excessive exposure to radiation. To overcome these problems, we propose a computer aided catheter selection
procedure. In this paper we present our approach for the angiography of the Right Coronary Artery (RCA).
Our approach involves segmentation of the aorta and coronary arteries, finding the centerline and computing the
Curve Angle (CA) and Curve Length (CL) between the aorta and the coronary arteries. We then compute CA
and CL of catheters and suggest a catheter with the closest CA and CL with respect to the aorta's and coronary
arteries' CA and CL. This solution avoids testing of many catheters during catheterization. The cardiologist
already gets the recommendation about the optimal catheter for the patient prior to the intervention.
In cardiac MR images the slice thickness is normally greater than the pixel size within the slices. In general,
better segmentation and analysis results can be expected for isotropic high-resolution (HR) data sets. If two
orthogonal data sets, e. g. short-axis (SA) and long-axis (LA) volumes are combined, an increase in resolution
can be obtained.
In this work we employ a super-resolution reconstruction (SRR) algorithm for computing high-resolution data
sets from two orthogonal SA and LA volumes. In contrast to a simple averaging of both data in the overlapping
region, we apply a maximum a posteriori approach. There, an observation model is employed for estimating an
HR image that best reproduces the two low-resolution input data sets.
For testing the SRR approach, we use clinical MRI data with an in-plane resolution of 1.5 mm×1.5 mm and
a slice thickness of 8 mm. We show that the results obtained with our approach are superior to currently used
averaging techniques. Due to the fact that the heart deforms over the cardiac cycle, we investigate further, how
the replacement of a rigid registration by a deformable registration as preprocessing step improves the quality
of the final HR image data. We conclude that image quality is dramatically enhanced by applying an SRR
technique especially for cardiac MR images where the resolution in slice-selection direction is about five times
lower than within the slices.