In conclusion, the results show that our CAD tool can generate patient-specific implants with high accuracy.

The correct visualization of anatomical structures is a critical component of neurosurgical navigation systems, to guide the surgeon to the areas of interest as well as to avoid brain damage. A major challenge for neuronavigation systems is the brain shift, or deformation of the exposed brain in comparison to preoperative Magnetic Resonance (MR) image sets. In this work paper, a non-rigid deformation pipeline is proposed for brain shift compensation of preoperative imaging datasets using superficial blood vessels as landmarks. The input was preoperative and intraoperative 3D image sets of superficial vessel centerlines. The intraoperative vessels (obtained using 3 Near-Infrared cameras) were registered and aligned with preoperative Magnetic Resonance Angiography vessel centerlines using manual interaction for the rigid transformation and, for the non-rigid transformation, the non-rigid point set registration method Coherent Point Drift. The rigid registration transforms the intraoperative points from the camera coordinate system to the preoperative MR coordinate system, and the non-rigid registration deals with local transformations in the MR coordinate system. Finally, the generation of a new deformed volume is achieved with the Thin-Plate Spline (TPS) method using as control points the matches in the MR coordinate system found in the previous step. The method was tested in a rabbit brain exposed via craniotomy, where deformations were produced by a balloon inserted into the brain. There was a good correlation between the real state of the brain and the deformed volume obtained using the pipeline. Maximum displacements were approximately 4.0 mm for the exposed brain alone, and 6.7 mm after balloon inflation.

Figure 1: Lateral view of the positions where the enclosed object (simulated tumor) is located within the exterior object (brain). Back position (left), center position(middle), front position(right). Two rendering methods were used with different opacity values. AbstractDepth perception of semi-transparent virtual objects and the visualization of their spatial layout are crucial in many applications, in particular medical applications. Depth cues for opaque objects have been extensively studied, but this is not the case for stereoscopic semi-transparent objects, in particular in the case when one 3D object is enclosed within a larger exterior object.In this work we explored different stereoscopic rendering methods to analyze their impact on depth perception accuracy of an enclosed 3D object. Two experiments were performed: the first tested the hypotheses that depth perception is dependent on the color blending of objects (opacity -alpha) for each rendering method and that one of two rendering methods used is superior. The second experiment was performed to corroborate the results of the first experiment and to test an extra hypothesis: is depth perception improved if an auxiliary object that provides a relationship between the enclosed object and the exterior is used?The first rendering method used is simple alpha blending with Blinn-Phong shading model, where a segmented brain (exterior object) and a synthetic tumor (enclosed object) were blended. The second rendering method also uses Blinn-Phong, but the shading was modified to preserve silhouettes and to provide an illustrative rendering. Comparing both rendering methods, the brighter regions of the first rendering method will become more transparent in the second rendering method, thus preserving silhouette areas.The results show that depth perception accuracy of an enclosed object rendered with a stereoscopic system is dependent on opacity for some rendering methods (simple alpha blending), but this effect is less pronounced than the dependence on object position in relation to the exterior object. The illustrative rendering method is less dependent on opacity. The different rendering methods also perform slightly differently; an illustrative rendering method was * superior and the use of an auxiliary object seems to facilitate depth perception.

Abstract. We aim at reconstructing superficial vessels of the brain. Ultimately, they will serve to guide the deformation methods to compensate for the brain shift. A pipeline for three-dimensional (3-D) vessel reconstruction using three mono-complementary metal-oxide semiconductor cameras has been developed. Vessel centerlines are manually selected in the images. Using the properties of the Hessian matrix, the centerline points are assigned direction information. For correspondence matching, a combination of methods was used. The process starts with epipolar and spatial coherence constraints (geometrical constraints), followed by relaxation labeling and an iterative filtering where the 3-D points are compared to surfaces obtained using the thin-plate spline with decreasing relaxation parameter. Finally, the points are shifted to their local centroid position. Evaluation in virtual, phantom, and experimental images, including intraoperative data from patient experiments, shows that, with appropriate camera positions, the error estimates (root-mean square error and mean error) are ∼1 mm.

Web-based teaching via Intelligent Tutoring Systems (ITSs) is considered as one of the most successful enterprises in artificial intelligence. Indeed, there is a long list of ITSs that have been tested on humans and have proven to facilitate learning, among which we may find the well-tested and known tutors of algebra, geometry, and computer languages. These ITSs use a variety of computational paradigms, as production systems, Bayesian networks, schematemplates, theorem proving, and explanatory reasoning. The next generation of ITSs are expected to go one step further by adopting not only more intelligent interfaces but will focus on integration. This article will describe some particularities of a tutoring system that we are developing to simulate conversational dialogue in the area of Medicine, that enables the integration of highly heterogeneous sources of information into a coherent knowledge base, either from the tutor's point of view or the development of the discipline in itself, i.e. the system's content is created automatically by the physicians as their daily work goes on. This will encourage students to articulate lengthier answers that exhibit deep reasoning, rather than to deliver straight tips of shallow knowledge. The goal is to take advantage of the normal functioning of the health care units to build on the fly a knowledge base of cases and data for teaching and research purposes.

Abstract. We aim at reconstructing superficial vessels of the brain. Ultimately, they will serve to guide the deformation methods to compensate for the brain shift. A pipeline for three-dimensional (3-D) vessel reconstruction using three mono-complementary metal-oxide semiconductor cameras has been developed. Vessel centerlines are manually selected in the images. Using the properties of the Hessian matrix, the centerline points are assigned direction information. For correspondence matching, a combination of methods was used. The process starts with epipolar and spatial coherence constraints (geometrical constraints), followed by relaxation labeling and an iterative filtering where the 3-D points are compared to surfaces obtained using the thin-plate spline with decreasing relaxation parameter. Finally, the points are shifted to their local centroid position. Evaluation in virtual, phantom, and experimental images, including intraoperative data from patient experiments, shows that, with appropriate camera positions, the error estimates (root-mean square error and mean error) are ∼1 mm.

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This paper presents a solution to minimize a problem that normally arises from the huge amount of images that a radiologist usually has to interpret. A multi-agent system that implements a multi-display for medical imaging based on computer clustering of normal personal computers is therefore described, as well as the multi-agent architecture that caters for the system evolution. An evaluation study was performed and its results are presented.