Research Projects (2005)
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- 3D Computer Vision 3D reconstruction Aerial Vision Augmented Reality Augmented Video Best Paper Award Biometrics Caleydo Computer Graphics Computer Vision Convex Optimization Coordinate transformations detection face Fingerprint Georeferencing GPU GUI HOG Human Computer Interaction Image Labelling Industrial Applications Information Visualization integral imaging Interaction Interaction Design Machine Learning Medical computer vision Medical Visualization Mixed Reality Mobile computing Mobile phone Model Multi-Display Environments Multiple Perspectives Object detection Object recognition Object reconstruction Object Tracking On-Line Learning Robotics Segmentation Shape analysis shape from focus SLAM Software Projects Structure from Motion Surveillance SVM Symmetry Tracking Fusion Tracking, Action Recognition User Interfaces Variational Methods Virtual reality and augmented reality Visual Tracking Visualization
ARIS*ER - Augmented Reality in Surgery
ARIS*ER is a Marie Curie Research Training Network addressing a cross-disciplinary area, critically in need of developing researchers with the understanding of the cross-cutting issues involved in developing tools for Minimally Invasive Therapy. The multidisciplinary consortium, aims at providing training for young researchers through a structured training and knowledge transfer program – that will provide Europe with human resources with knowledge that will lead to better healthcare to citizens in Europe. The particular focus of the research training and joint project will be software that is user-friendly, fast and reliable for the practitioners of minimal invasive therapy (MIT). MIT is a compound of minimally invasive surgery, image guided surgery and interventional radiology. MIT makes use of numerous sources of information including multi-modal images and patient information systems. Intelligent processing of this information comprises a vast pool of knowledge that can aid the operator in his decisions. The ultimate goal of the joint project, which will give the recruited researcher training-by-doing, is to create an Augmented Reality system for interactive image guided therapy providing the clinical user with a new generation of decision support tools. This system will integrate intra-operative and pre-operative image-information and enable the user to see beyond the organ surface to inner structures and pathology. An intuitive human computer interface consisting of 3D display systems, haptics and robotics will hide the underpinning complexity of the decision support tools. Demonstrators will be made aiming at providing a seamless workflow for the clinical user conducting image-guided therapy.