SU-E-T-754: Three-Dimensional Patient Modeling Using Photogrammetry for Collision Avoidance

Authors


Abstract

Purpose:

To evaluate photogrammetry for creating a three-dimensional patient model.

Methods:

A mannequin was configured on the couch of a CT scanner to simulate a patient setup using an indexed positioning device. A CT fiducial was placed on the indexed CT table-overlay at the reference index position. Two dimensional photogrammetry targets were placed on the table in known positions. A digital SLR camera was used to obtain 27 images from different positions around the CT table. The images were imported into a commercial photogrammetry package and a 3D model constructed. Each photogrammetry target was identified on 2 to 5 images. The CT DICOM metadata and the position of the CT fiducial were used to calculate the coordinates of the photogrammetry targets in the CT image frame of reference. The coordinates were transferred to the photogrammetry software to orient the 3D model. The mannequin setup was transferred to the treatment couch of a linear accelerator and positioned at isocenter using in-room lasers. The treatment couch coordinates were noted and compared with prediction. The collision free regions were measured over the full range of gantry and table motion and were compared with predictions obtained using a general purpose polygon interference algorithm.

Results:

The reconstructed 3D model consisted of 180000 triangles. The difference between the predicted and measured couch positions were 5 mm, 1 mm, and 1 mm for longitudinal, lateral, and vertical, respectively. The collision prediction tested 64620 gantry table combinations in 11.1 seconds. The accuracy was 96.5%, with false positive and negative results occurring at the boundaries of the collision space.

Conclusion:

Photogrammetry can be used as a tool for collision avoidance during treatment planning. The results indicate that a buffer zone is necessary to avoid false negatives at the boundary of the collision-free zone. Testing with human patients is underway.

Research partially supported by a grant from Varian Medical Systems

Ancillary