Illustrative stream surfaces.

Stream surfaces are an intuitive approach to represent 3D vector fields. In many cases, however, they are challenging objects to visualize and to understand, due to a high degree of self-occlusion. Despite the need for adequate rendering methods, little work has been done so far in this important research area. In this paper, we present an illustrative rendering strategy for stream surfaces. In our approach, we apply various rendering techniques, which are inspired by the traditional flow illustrations drawn by Dallmann and Abraham \& Shaw in the early 1980s. Among these techniques are contour lines and halftoning to show the overall surface shape. Flow direction as well as singularities on the stream surface are depicted by illustrative surface streamlines. ;To go beyond reproducing static text book images, we provide several interaction features, such as movable cuts and slabs allowing an interactive exploration of the flow and insights into subjacent structures, e.g., the inner windings of vortex breakdown bubbles. These methods take only the parameterized stream surface as input, require no further preprocessing, and can be freely combined by the user. We explain the design, GPU-implementation, and combination of the different illustrative rendering and interaction methods and demonstrate the potential of our approach by applying it to stream surfaces from various flow simulations. ;

Validation of 3D-laser surface registration for image-guided cranio-maxillofacial surgery.

AIM: Image-data-based navigation plays an important role during surgical treatment in anatomically complex areas. Conventional patient-to-image registration techniques on the basis of skin and bone markers require expensive and time-consuming logistic support. A new markerless, high-resolution laser surface scan technique for patient registration has been tested in experimental and clinical settings. METHODS: In a phantom study, a skull model was registered with laser scanning and marker-based algorithms. The registration procedure was repeated 25 times in each group. The values for the root mean-square error were calculated as a measure of the deviation of the forecast position from the actual position and the target difference. In a clinical setting, 21 consecutive patients who presented with cranio-maxillofacial disorders were scheduled for navigational surgery using laser surface scanning for patient-to-image registration. Here the accuracy was determined by anatomical landmark localization. RESULTS: In the experimental study, a root mean-square error of 1.3+/-0.14 mm, and a mean target deviation of 2.08+/-0.49 mm were found for laser scanning. In contrast, a root mean-square error of 0.38+/-0.01 mm and a mean target deviation of 0.99+/-0.15 mm were found for marker registration. The differences were statistically significant (p<0.005). A strong correlation between the root mean-square error and the target deviation was found for laser (r=0.96) and marker registration (r=0.95). During the 21 clinical procedures, the overall accuracy of laser scan registration determined by the root mean-square error was 1.21+/-0.34 mm, and the mean clinical precision was 1.8+/-0.5 mm. CONCLUSIONS: Three-dimensional laser surface registration offers an interesting approach for selected image-guided procedures in cranio-maxillofacial surgery.

Hybrid segmentation and virtual bronchoscopy based on CT images.

RATIONALE AND OBJECTIVES: Introduction of combination of the segmentation tool SegoMeTex and the virtual endoscopy system VIVENDI to perform virtual endoscopic inspections of the human lung. This virtual bronchoscopy system enables visualization of the tracheobronchial tree down to seventh generation. Furthermore, the modified virtual system visualizes hidden structures such as segmented vascular system or tumors. MATERIALS AND METHODS: The segmentation is based on image data acquired by a multislice computed tomography scanner. SegoMeTex is used to segment the tracheobronchial tree by a hybrid system with minimal user action. Similarly, the complementary pulmonary arterial can be segmented, whereas additional structures such as tumors are marked manually. On this dataset, subsequently, data structures of the inner surface for virtual endoscopy are generated. Finally, the dataset can be explored by a virtual bronchoscopy procedure using the VIVENDI system. RESULTS: The segmentation method was successfully tested on 22 patients. The hybrid segmentation system identified bronchi up to the sixth generation with a sensitivity of more than 58%, and a positive predictive value of more than 90%. After the segmentation, the datasets are explored interactively (>30 fps on a standard personal computer platform in real-time rendering) using the virtual endoscopy software. The exploration exposed a high-quality reconstruction, even of small structures throughout the dataset. CONCLUSION: Virtual bronchoscopy in combining with a highly sensitive segmentation is a valuable tool for the localization and measurement of stenosis for resection planning.

Simultaneous virtual representation of both vascular and neural tissue within the subarachnoid space of the basal cistern--technical note.

BACKGROUND: The representation of different anatomical structures requires varying imaging modalities and protocols. By mental composition of single-slice images, a three-dimensional (3D) impression can be achieved. However, this presupposes an outstanding imagination and is subject to inaccuracies. The use of an interactive and multi-modal planning system which represents different data sets in one single virtual environment holds promise to facilitate and improve neurosurgical decision-making. The authors report the clinical application of a self-developed virtual planning system in a case of trigeminal neuralgia due to an ectatic basilar artery. MATERIAL/METHODS: We modified our virtual planning system (VIVENDI), to achieve a virtual representation of the basal cistern illustrating both vascular and neuronal information. After conducting several experiments to determine an appropriate scanning protocol, we matched the data achieved by magnetic resonance imaging (MRI) and magnetic resonance angiography (MRA). RESULTS: The system provides the vascular topography combined with information on the anatomical structure of the subarachnoid space. To illustrate the clinical usefulness of this planning approach, the authors present a case of trigeminal neuralgia caused by an ectatic basilar artery. Pre-operatively, the virtual representation returned accurate information on the anatomical configuration of the cerebellopontine angle and the course of the ectatic vessel. This information was confirmed during surgery. CONCLUSIONS: The presented case demonstrates the clinical applicability of VIVENDI within the subarachnoid space of the basal cistern. The virtual representation enables pre-operative planning and simulation based on the patient's individual anatomy.