3-D Endoscopy is an evolving field of research and offers great benefits for minimally invasive procedures. Besides the pure topology, color texture is an inevitable feature to provide an optimal visualization. Therefore, in this paper, we propose a sensor fusion of a Time-of-Flight (ToF) and an RGB sensor. This requires an intrinsic and extrinsic calibration of both cameras. In particular, the low resolution of the ToF camera (64x50 px) and inhomogeneous illumination precludes the use of standard calibration techniques. By enhancing the image data with the use of self-encoded markers for automatic checkerboard detection, a re-projection error of less than 0.23 px for the ToF camera was achieved. The relative transformation of both sensors for data fusion was calculated in an automatic manner.

The combination of parallel MRI techniques with compressed sensing ideas is an active field of research. The expected benefit is a gain in aquisition time. The aim of this work is to compare different sampling schemes for highly undersampled non-contrast-enhanced MR angiography (MRA) and to derive an optimized scheme in the combination with iterative reconstruction. In this context, an inverse root pattern is proposed for optimized artifact removal and vessel delineation.

Experiments showed that the image quality obtained with the iterative reconstruction is highly dependent on the chosen pattern. With the inverse root pattern, it was possible to obtain high-quality results at very high undersampling factors.

Motion during data acquisition is an ongoing challenge in MRI. Sadly, motion is often worst in patients that are acutely ill and in which time cannot be afforded to repeat failed exams. This is the case, for example, in patients suffering from acute ischemic stroke or intracranial hemorrhages. For diagnosis of these patients often 3D Time of Flight (TOF) angiograms are performed. Due to unintentional head motion during data acquisition image quality may be degraded or even draw an image non-diagnostic. To mitigate motion artifacts different retrospective and prospective approaches have been suggested. However, these approaches most often require extra navigator data, which can substantially increase sequence TR. 

In this work, a prospective motion-correction system is proposed which adapts the scan geometry to patient pose changes in real-time. The pose updates are obtained from a MR compatible camera tracking a self-encoded marker. First experiments were performed with three consecutive scans each consisting of a single 7.7cm 3D slab that covers the Circle of Willis. The resulting images are shown in Figure 1. In the first scan, a motion free reference scan was acquired, while in the following scans a specific motion pattern was performed. Motion during the data acquisition remained uncorrected for the second and correct for the third scan.

First preliminary results show that the proposed system is very effective in correction motion-induced artifacts.