Automated breathing motion tracking for 4D computed tomography

4D-CT is being developed to provide breathing motion information for radiation therapy treatment planning. Potential applications include optimization of intensity-modulated beams in the presence of breathing motion and intra-fraction target volume margin determination for conformal therapy. A major challenge of this process is the determination of the internal motion (trajectories) from the 4D CT data. Manual identification and tracking of internal landmarks is impractical. For example, in a single couch position, 512 /spl times/ 512 /spl times/ 12 pixel CT scans contains 3.1/spl times/10/sup 5/ voxels. If 15 of these scans are acquired throughout the breathing cycle, there are almost 47 million voxels to evaluate necessitating automation of the registration process. The natural high contrast between bronchi, vessels, other lung tissue offers an excellent opportunity to develop automated deformable registration techniques. We have been investigating the use motion compensated temporal smoothing using optical flow for this purpose. Optical flow analysis uses the CT intensity and temporal (in our case tidal volume) gradients to estimate the motion trajectories. The algorithm is applied to 3D image datasets reconstructed at different percentiles of tidal volumes. The trajectories can be used to interpolate CT datasets between tidal volumes.