- Show Keywords
- 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
Virtual Liver Surgery Planning
Resection is the treatment of choice for patients suffering from liver tumors. Knowledge about involved liver segments, tumor size and topographic relationship of the tumor to vessels is needed for the decision if sufficient liver function capacity is guaranteed after a resection and for detailed planning of a possible resection. The main information sources are cross sectional imaging modalities like CT which deliver 2D images. The radiologist has thus to put all the information of the cross sectional images together in order to provide the surgeons with the needed information about the 3D topology. This process is difficult, tedious and time consuming. Combining the methods of medical computer vision and graphics a liver surgery planning system can be developed that enables a better overview and thus helps unfolding the full potential of surgical methods. Available approaches show that a number of improvements, specially on the fields of automation of segmentation and user friendly visualization are necessary to attain clinical applicability and gain the full acceptance by radiologists and surgeons. The goal of this research project is to develop an experimental environment for the staging of liver operations. Special efforts will be put on two issues. First, a fully automated segmentation of the liver, its vessels and tumors will be studied. Second, the environment for the interactive, cooperative visualization of the medical sensor data, the extracted anatomical structures, and for the use of tools to assess the best surgical approach will be developed and assessed. After development, the approaches for segmentation/partitioning, visualization and interactive resection will undergo a careful validation procedure.