Search results for "Virtual patient"
showing 3 items of 3 documents
Three-dimensional Cross-Platform Planning for Complex Spinal Procedures
2017
STUDY DESIGN A feasibility study. OBJECTIVE To develop a method based on the DICOM standard which transfers complex 3-dimensional (3D) trajectories and objects from external planning software to any navigation system for planning and intraoperative guidance of complex spinal procedures. SUMMARY OF BACKGROUND DATA There have been many reports about navigation systems with embedded planning solutions but only few on how to transfer planning data generated in external software. MATERIALS AND METHODS Patients computerized tomography and/or magnetic resonance volume data sets of the affected spinal segments were imported to Amira software, reconstructed to 3D images and fused with magnetic reson…
Clinically-Driven Virtual Patient Cohorts Generation: An Application to Aorta
2021
The combination of machine learning methods together with computational modeling and simulation of the cardiovascular system brings the possibility of obtaining very valuable information about new therapies or clinical devices through in-silico experiments. However, the application of machine learning methods demands access to large cohorts of patients. As an alternative to medical data acquisition and processing, which often requires some degree of manual intervention, the generation of virtual cohorts made of synthetic patients can be automated. However, the generation of a synthetic sample can still be computationally demanding to guarantee that it is clinically meaningful and that it re…
Segmentation and Navigation Support of Clinical Data Sets to Simulate the Bronchoscopy and Rhinoscopy
2007
A training and simulation system for therapy planning is developed based on patient specific imaging data. A real endoscope is used for navigation through the virtual patient. For this purpose sensors were built in the endoscope in order to track the translation, rotation and the angle of the distal end. Pre-processing (segmentation, tissue characterization) speeds-up the volume rendering up to real-time. Collision detection enables a realistic fly through the virtual patient.