Iterative sorting for 4DCT images based on internal anatomy motion

Geometric uncertainties caused by respiratory motion com-plicate radiotherapy treatment planning. Therefore 4D CT imaging is important in characterizing anatomy motion dur-ing breathing. Current 4D CT imaging techniques using multi-slice CT scanners involve multiple scans at several axial posi-tions and retrospective sorting processes. Most sorting meth-ods are based on externally monitored signals recorded by external monitoring instruments, which may not always accu-rately catch the actual breathing status and may lead to severe discontinuity artifacts in the sorted CT volumes. We propose a method to reconstruct time-resolved CT volumes based on internal motion to avoid the inaccuracies caused by external breathing signals. In our method, we iteratively sort the 4D CT slices using internal motion based breathing indices. In each iteration, respiratory motion is estimated by updating a motion model to best match a deformed reference volume to each moving multi-slice sub-volumes. The breathing indices as well as the reference volumes are refined for each iteration based on the currently estimated respiratory motion. An ex-ample is presented to illustrate the feasibility of our 4D CT sorting method without using any external motion monitoring systems. Index Terms — 4D CT, motion estimation, registration, amplitude sorting 1