Biomedical subjects
Publications and source records attributed to Heinz Wörn.
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.
Computer- and robot-based systems to support interventions become more and more important in modem surgery. In general these systems provide methods to plan an intervention pre-operatively and to execute it with support from a autonomous robot-system. Due to the principle restriction of a robot to comparatively simple work steps, there are some complex work steps which the surgeon may plan but which he/she has to execute manually. In craniofacial surgery osteotomised bone segments are deformed by hand to a shape given by the planning system. We support the execution of pre-planned deformation by comparison of the actual shape of an object with the target shape. The actual shape is obtained intra-operatively with a surface scanning device, the deviation from the target shape are visualised by projecting colour-coded error values directly on the object to be deformed. The surgeon uses these projections to adjust further deformation steps. The system is therefore able to validate the correct execution of planned deformations, especially of bony structures.
Normative data is very important for simulation procedures in craniofacial surgery. While treating e.g. a malformed skull the surgeon seeks to reconstruct its natural and harmonic shape. Atlas or normative data of the skull could support the surgeon in this effort, as it would provide a standard model of the skull which gives an idea of the natural shape. We create a standard skull by averaging regularly formed skulls in a shape space spanned by spherical harmonics. While state-of-the-art methods use landmarks to define the shape and mean shapes, this method is deterministic, i.e. it manages averaging without landmarks and it provides a complete description of the shape. In addition the shape space can be used to classify shapes to identify different types of an anatomy.
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.
With the new computer aided surgery techniques a surgery can be split in two phases, which are pre-operative planning and intervention. The planning is frequently based on three dimensional image data and takes place in the office of the surgeon. Using this approach the surgical feeling, the physical feedback of the patient, is not available during the planning phase. However, this feedback yields information, which is helpful or necessary for the planning. This lack of information can be compensated by a simulation module, which simulates kinematic data from image volume data. To develop such a module first both image volume data and kinematic data have to be captured from a wide range of patients. In this work a new approach for kinematic analysis of the knee is presented which yields an accuracy which is necessary for such simulation. Because the analysis has to be done for many patients the degree of invasiveness is emphasized. This contactless and non invasive approach is based on external fixations, anatomical skin markers, video sequences and computer tomograms. Position tracking of femur and tibia for any motion pattern is possible. Because the individual anatomic structures extracted from the tomogram are tracked, an analysis of any point or coordinate system can be done later using the originally captured data. This gives a new degree of freedom for analysis.