3D warping and registration from lung images

Computerized volumetric warping and registration of 3D lung images can provide objective, accurate, and reproducible measures to the understanding of human lung structure and function. It is also invaluable to the assessment of the presence of diseases and their response to therapy. However, due to the complexity of breathing motion, little work has been carried out in this research area. In this paper, we propose a novel scheme to implement volumetric lung warping and registration from 3D CT images obtained at different stages of breathing. Bronchial points of airway trees and vessels are selected as feature points since they can be easily tracked over consecutive frames. The warping of these feature points into the entire volume is obtained based on a model of continuum mechanics and is implemented in an iteration fashion governed by such model. The model consists of three constraints: an incompressibility constraint, a divergence-free constraint and a motion-discontinuity-preserving smoothness constraint. An objective function is defined as a weighted sum of the three constraint terms and the desired displacement field of the whole volume between different stage of breathing is obtained by minimizing this objective function. The 3D warping is therefore represented by the dense displacement field obtained from the iteration. Preliminary results are visualized by overlaying the displacement field with the original images. Effectiveness of the algorithm is also evaluated by comparing the volume difference between the real and warped volumes. We believe the proposed approach will open up several areas of research in lung image analysis that can make use of the results from warping lung volumes.