Biomedical subjects
Publications and source records attributed to Jörg Raczkowsky.
Augmented Reality (AR) is a promising tool for intraoperative visualization. Two different AR systems, one projector based, one based on see-through glasses were used on patients. The task was the transfer of preoperative planning into the intraoperative reality, or the visualization of space occupying lesions, respectively. The intraoperative application of both systems is discussed from the surgeons point of view.
For visualizing surgical information (operation plans) directly onto the patient a projector-based augmented reality system is used for cranio-maxillofacial surgery. A prototype is introduced which has been evaluated in the first clinical cases. In a new setup with a second video projector it is now possible to give additionally 3D information for localization and orientation (6DoF). With this method the repositioning of a bone segment is intuitive and exact applicable.
OBJECTIVE: Today's surgical robots normally perform "simple" trajectories, e.g., assisting as tool-holding devices in neurosurgery, or milling linear paths for cavities in total hip replacement. From a clinical point of view, it is still a complex undertaking to implement robots in the operating room. Until now, robot systems have not been used in patient trials to mill "complex" trajectories, which involve many positional and orientation changes and are often necessary in cranio-maxillofacial (CMF) surgery. This paper presents the RobaCKa surgical robot system, which allows more precise execution of surgical interventions and milling of "complex" trajectories. MATERIALS AND METHODS: The main components of the RobaCKa system are a (former) CASPAR robot system, a POLARIS system, and a force-torque sensor. RESULTS: In the first patient trial (April 2003) the planned trajectory was executed with an error of 0.66 +/- 0.2 mm. CONCLUSIONS: The use of former industrial robots for surgical applications is possible but complex. The advantages are improved precision and quality and the possibility of documentation. The use of such systems is normally limited to research institutions or large clinics, because it is hardly possible to implement the necessary technical and logistic efforts in routine surgical work.
Efficiency, comparability and simplicity are key aspects for user acceptance of surgical planning systems in the long term. Automatic segmentation and identification of geometric reference systems of the anatomical structures are essential to fulfill these requirements. A statistical motivated shape atlas of the knee joint, based on 235 normal and abnormal MR and CT volume sets, is constructed for automatic segmentation of CT image data. In the first step of the atlas construction, the bony structures of the knee were segmented semi-automatically and processed into a dense and a sparse triangulated surface mesh to obtain training data sets. To establish an inter-individual correspondence, a skeleton-based registration method is used. The registered sparse surface meshes are retriangulated to estimate a pointwise inter-individual correspondence. The shape atlas is build upon these correspondences and integrated into a segmentation algorithm. An iterative segmentation scheme is proposed, which consists of a combination of the iterative-closest-point algorithm for spatial registration and of a downhill-simplex optimization procedure for deformation of the statistical motivated shape atlas to the image data. We expect the statistical shape model to be a robust and image modality independent method for the segmentation of pathological knee joints in CT image data.
In 2000, the Institute for Process Control and Robotics/Universität Karlsruhe (TH) has developed a prototype system for projector based augmented reality consisting of a state-of-the-art PC, two CCD cameras and a video projector which is used for registration and projection of surgical planning data. Tracking, registration as well as projection require an accurate calibration process for cameras and video projectors. We have developed a new, flexible, plain and easy to implement model, which can both be used for calibration of cameras and video projectors.
Realistic visualisation becomes more and more important in medicine. Whenever a patient individual 3D-model was generated the aim is to visualise the model as realistic as possible. We use 3D-models in our diagnostic and therapeutic tools for intraoperative visualisation of e.g. CT-scans. Most medical tools uses surface-rendering or volume-rendering for virtual visualisation. The coloration of a visualised model is normally done by using a convenient colour for each surface resp. volume. Our approach for 3D-models generated from motion in image series (e.g. videoendoscopes) is to add textures to the 3D-model. The main problem is, to handle the huge amount of videoimage-data (20Mb/sec.) and render the model in realtime.
Endoscopy is an important procedure for the diagnostic and therapy of various pathologies. In 2000, the Institute for Process Control and Robotics/Universität Karlsruhe (TH) has developed a basic framework for reconstructing 3D models from image sequences. The framework is able to realise automatic navigation for new colonoscopes with own driving system and on the other hand to offer a virtual 3D endoscopic view during bad visibility conditions caused by e.g. abrupt bleeding. This method generates a 3D-model intraoperatively compared to preoperatively generated 3D-models in virtual endoscopy.