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Collision Avoidance Mapping Using Consumer 3D Camera

R Cardan

R Cardan*, R Popple , Univ Alabama Birmingham, Birmingham, AL


SU-F-BRB-5 (Sunday, July 12, 2015) 4:00 PM - 6:00 PM Room: Ballroom B

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.

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.

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.

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.

Funding Support, Disclosures, and Conflict of Interest: Research partially supported by a grant from Varian Medical Systems

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