SU-F-BRB-05: Collision Avoidance Mapping Using Consumer 3D Camera

Authors


Abstract

Purpose:

To develop a fast and economical method of scanning a patient's full body contour for use in collision avoidance mapping without the use of ionizing radiation.

Methods:

Two consumer level 3D cameras used in electronic gaming were placed in a CT simulator room to scan a phantom patient set up in a high collision probability position. A registration pattern and computer vision algorithms were used to transform the scan into the appropriate coordinate systems. The cameras were then used to scan the surface of a gantry in the treatment vault. Each scan was converted into a polygon mesh for collision testing in a general purpose polygon interference algorithm. All clinically relevant transforms were applied to the gantry and patient support to create a map of all possible collisions. The map was then tested for accuracy by physically testing the collisions with the phantom in the vault.

Results:

The scanning fidelity of both the gantry and patient was sufficient to produce a collision prediction accuracy of 97.1% with 64620 geometry states tested in 11.5 s. The total scanning time including computation, transformation, and generation was 22.3 seconds.

Conclusion:

Our results demonstrate an economical system to generate collision avoidance maps. Future work includes testing the speed of the framework in real-time collision avoidance scenarios.

Research partially supported by a grant from Varian Medical Systems

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