Analysis of Collision Detection Using Implicit Sphere Tree in Saptic Interaction Environments for Maxillofacial Surgery Applications

doi:10.1109/CISP-BMEI.2018.8633199

Paper

Analysis of Collision Detection Using Implicit Sphere Tree in Saptic Interaction Environments for Maxillofacial Surgery Applications

Published Oct 1, 2018 · Laurens Le Jeune, W. Swinkels, Yi Sun

2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)

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Abstract

Facial malformations such as overbite or underbite can be treated by maxillofacial surgery where the mandibula (i.e. the lower jaw) and/or maxilla (i.e. the upper jaw) is repositioned to obtain a preferential occlusion. These treatments need to be carefully planned prior to the actual operation. The planning of such surgery is an intensive and time consuming procedure in which the experience and knowledge of the surgeon plays a major role. As part of a CAD-based surgery planning, haptic interaction using 3D virtual models of the mandibula and maxilla, haptic feedback can make planning and surgery much more efficient. Haptic devices bridge the gap between the virtual environment and the physical world. An important step in such haptics based workflow is the collision detection between the two models at an update frequency of at least 1000 Hz. In this paper the possibility of the Implicit Sphere Tree algorithm as a collision detection algorithm tailored for this specific application is presented.

Study Snapshot

The Implicit Sphere Tree algorithm can efficiently detect collisions between 3D virtual models in haptic interaction environments, making maxillofacial surgery planning and surgery more efficient.

PopulationOlder adults (50-71 years)

Sample size24

MethodsObservational

OutcomesBody Mass Index projections

ResultsSocial networks mitigate obesity in older groups.

Paper

Analysis of Collision Detection Using Implicit Sphere Tree in Saptic Interaction Environments for Maxillofacial Surgery Applications

References

Haptic collision detection on highly complex medical data structures

The Inner Sphere Tree data structure, with optimized tree traversal algorithms, enables efficient collision detection in orthognathic surgery digital planning workflows, achieving the required update speed of at least 1 kHz for haptic feedback devices.

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This paper presents a new data structure for collision detection and haptics, enabling the computation of penetration volumes, improving performance and quality in various applications.

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This paper presents a real-time collision detection algorithm using spherical octrees, which accurately detects potential collisions between three-dimensional moving objects in virtual reality, maintaining linear performance with object complexity.

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Our force-feedback software library effectively integrates force feedback into real-time virtual environments, providing benefits such as haptic-textured surfaces, device independence, distributed operation, and easy enhancement.

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The new collision detection algorithm provides acceptable accuracy while maintaining a steady and high frame rate, improving performance in interactive graphics applications like vehicle simulators and virtual reality.

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