P.J.H. de Koning

Automated segmentation and analysis of vascular structures in magnetic resonance angiographic images.

The accurate assessment of the presence and extent of vascular disease, and planning of vascular interventions based on MRA requires the determination of vessel dimensions. The current standard is based on measuring vessel diameters on maximum intensity projections (MIPs) using calipers. In order to increase the accuracy and reproducibility of the method, automated analysis of the 3D MR data is required. A novel method for automatically determining the trajectory of the vessel of interest, the luminal boundaries, and subsequent the vessel dimensions is presented. The automated segmentation in 3D uses deformable models, combined with knowledge of the acquisition protocol. The trajectory determination was tested on 20 in vivo studies of the abdomen and legs. In 93% the detected trajectory followed the vessel. The luminal boundary detection was validated on contrast‐enhanced (CE) MRA images of five stenotic phantoms. The results from the automated analysis correlated very well with the true diameters of the phantoms used in the in vitro study (r = 0.999, P < 0.001). MRA and x‐ray angiography (XA) of the phantoms also correlated well (r = 0.895, P < 0.001). The average unsigned difference between the MRA and XA measurements was 0.08 ± 0.05 mm. In conclusion, the automated approach allows the accurate assessment of vessel dimensions in MRA images. Magn Reson Med 50:1189–1198, 2003.

Evaluation of 2D and 3D glove input applied to medical image analysis

We describe a series of experiments that compared 2D/3D input methods for selection and positioning tasks related to medical image analysis. For our study, we chose a switchable P5 Glove Controller, which can be used to provide both 2DOF and 6DOF input control. Our results suggest that for both tasks the overall performance and accuracy can be improved when the input device with more degrees of freedom (DOF) is used for manipulation of the visualized medical data. 3D input turned out to be more beneficial for the positioning task than for the selection task. In order to determine a potential source of the difference in the task completion time between 2D and 3D input, we also investigated whether there was a significant difference between 2DOF and 6DOF input methods with regard to the time spent on task-specific basic manipulations.

3D cylindrical B-spline segmentation of carotid arteries from MRI images

The paper presents a segmentation method based on 3D cylindrical B-spline model. Proposed method was applied to 5 patient MRA studies of carotid arteries and 1 phantom dataset. Carotid bifurcation was segmented as two independent, overlapping branches. The presented method was evaluated against observer drawn contours and phantom model. Statistical assessment of vessel lumen area showed 10.4% systematic underestimation and good precision (SD = 9.2 vs. SDinterobs= 11.8) of presented method in comparison to the observers results

A framework for fast initial exploration of PC-MRI cardiac flow

Cardiac flow is still not fully understood, and is currently an active research topic. Using phase-contrast magnetic resonance imaging (PC-MRI) blood flow can be measured. For the inspection of such flow, researchers often rely on methods that require additional scans produced by different imaging modalities to provide context. This requires labor-intensive registration and often manual segmentation before any exploration of the data is performed. This work provides a framework that allows for a quick exploration of cardiac flow without the need of additional imaging and time-consuming segmentation. To achieve this, only the 4D data from one PC-MRI scan is used. A context visualization is derived automatically from the data, and provides context for the flow. Instead of relying on segmentation to deliver an accurate context, the hearts ventricles are approximated by half-ellipsoids that can be placed with minimal user interaction. Furthermore, seeding positions for flow visualization can be placed automatically in areas of interest defined by the user and based on derived flow features. The framework enables a user to do a fast initial exploration of cardiac flow, as is demonstrated by a use case and a user study involving cardiac blood flow researchers.

3D Quantification and visualization of MRA

Abstract A new method is presented to segment vessels in 3D MRA data, based on the wavefront propagation algorithm. We will compare the results to conventional X-ray DSA, and we will show our 3D visualization and interaction platform.