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Biomedical subjects

C R Burghart

Publications and source records attributed to C R Burghart.

3 recordsLinked to original sources

Computer aided planning device for preoperative bending of osteosynthesis plates.

In craniofacial surgery bone fractures and repositioned bone segments often have to be fixed by titanium miniplates. In clinical routines the surgeon has to fit each miniplate t be used to the individual bone structure of the patient: bending and fitting of a miniplate must frequently be repeated several times. Often up to twenty minutes are required to achieve the best fit of a single osteosynthesis plate. As a patient usually receive several miniplates for bone fixture, he will be exposed to long anaesthesia. In co-operation with the surgeons of the Clinic of Maxillofacial surgery at the University of Heidelberg we have conceived a planning system for the preoperative positioning of miniplates on a model of the patient's skull. The appropriate bending is computed and the bending data are stored for later use by a bending device and an intraoperative positioning aid. The principles of our computer-aided tool are presented in this paper.

Bone Plates↗

A system for robot assisted maxillofacial surgery.

In maxillofacial surgery the quality of the surgical outcome mainly depends on the experience of the operating surgeon. Thus we intend to support the surgeon before and during surgery in order to enhance the surgical results. On the one hand this implies the use of image processing, three dimensional modelling techniques and visualization techniques of medical image data, on the other hand planning systems, intraoperative navigation devices and surgical robots are needed. In this paper a complex expert system is presented, which uses a planner for generating treatment plans, an infrared navigation for monitoring both patient, robot, and surgical tool, and a surgical robotic system in order to work on bone. Special stress is laid on the architecture of the planning system, the structure of the treatment plans, and the intraoperative communication protocols.

Algorithms↗

Knowledgebased segmentation.

The segmentation of medical images like CT or MRI scans represents a great challenge to researchers in computer vision, due to the variability of the individual anatomy and the different characteristics of the scanning systems. As an anatomical knowledge base improves the recognition of structures in CT or MRI scans, we chose a knowledge based segmentation in our approach, which will be explained in the following.

Algorithms↗