Respiratory motion models aim at improving the quality of free breathing image acquisition protocols and yieldincreased targeting accuracy during image guided interventions. Respiratory motion can deviate pre-definedtargets and trajectories determined preoperatively during treatment procedures. In this context, motion modelsoffer a mean to estimate spatio-temporal displacements of the organ and correct the target position in real timeduring an intervention. To construct a motion model, data of the entire organ of interest must be acquired.However, existing techniques for 3D dynamic imaging have poor spatial and temporal resolution. Therefore,to capture the organ’s temporal behavior, series of dynamic 2D slices covering the entire organ are typicallyacquired. Then, these slices are reordered retrospectively according to their motion phase within the respiratorycycle and stacked to form 3D dynamic volumes known as 4D images (3D + t). On the other hand, while numerousmetrics were proposed to assess the spatial quality of the reordering, little attention has been paid to metricsthat assess the coherent temporal behavior of the reconstructed dynamic volumes. This work proposes a methodcombining image-based matching approach with manifold alignment and compares it with two state of the artslice reordering methods. Methods were evaluated on a dataset of 7 volunteers using new metrics to assess thespatial quality and the temporal behavior, with the proposed method outperforming in terms of both spatialand temporal quality.
展开▼
