An inverse hyper-spherical harmonics-based formulation for reconstructing 3D volumetric lung deformations |
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| Authors: | Anand P. Santhanam Yugang Min Sudhir P. Mudur Abhinav Rastogi Bari H. Ruddy Amish Shah Eduardo Divo Alain Kassab Jannick P. Rolland Patrick Kupelian |
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| Affiliation: | 1. College of Optics and Photonics, University of Central Florida, Orlando, FL 32816 2450, USA;2. College of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816 2450, USA;3. Concordia University, Canada;4. Department of Health and Public Affairs, University of Central Florida, Orlando, FL 32816 2450, USA;5. Department of Radiation Oncology, M.D. Anderson Cancer Center, Orlando, USA;6. Mechanical, Material and Aerospace Engineering, University of Central Florida, Orlando, FL 32816 2450, USA;7. Institute of Optics, University of Rochester, USA;8. Department of Radiation Oncology, University of California, Los Angeles, USA |
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| Abstract: | A method to estimate the deformation operator for the 3D volumetric lung dynamics of human subjects is described in this paper. For known values of air flow and volumetric displacement, the deformation operator and subsequently the elastic properties of the lung are estimated in terms of a Green's function. A Hyper-Spherical Harmonic (HSH) transformation is employed to compute the deformation operator. The hyper-spherical coordinate transformation method discussed in this paper facilitates accounting for the heterogeneity of the deformation operator using a finite number of frequency coefficients. Spirometry measurements are used to provide values for the airflow inside the lung. Using a 3D optical flow-based method, the 3D volumetric displacement of the left and right lungs, which represents the local anatomy and deformation of a human subject, was estimated from 4D-CT dataset. Results from an implementation of the method show the estimation of the deformation operator for the left and right lungs of a human subject with non-small cell lung cancer. Validation of the proposed method shows that we can estimate the Young's modulus of each voxel within a 2% error level. |
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