An Innovative Iterative Neighboring Volume Morphing Algorithm Based On Landmark Mesh to Create 3DCT During Treatment
H Wu1*, M Lu2, C Cheng3, (1) IUPUI, Indianapolis, IN, (2) PerkinElmer Imaging, Santa Clara, CA, (3) Indiana University- School of Medicine, Bloomington, INTU-G-141-7 Tuesday 4:30PM - 6:00PM Room: 141
Purpose: For the emerging 4D planning radiation treatment, 3DCT during treatment delivery is required. However, it is time consuming or impossible to acquire 3DCT during treatment delivery. This project will generate the 3DCT for any time instant based on a set of motion features (landmarks).
Methods: Previously acquired 4DCT is used for landmark selection. The landmarks are monitored in real-time during treatment delivery using two orthogonal x-ray images. For any set of landmarks acquired at target phase T, the 3DCT of the nearest 4DCT phase will be selected as the source phase S based on landmark mesh similarity. The iterative morphing algorithm has 8 steps based on neighboring density volume, including landmark selection, isosurface and tumor center identification, landmark mapping using weighted 3-layer mesh neighbors, landmark mesh similarity comparison, backward morphing based on density volume, and iterative volume morphing. It will generate the corresponding 3DCT at target phase.
Results: To validate the morphing algorithm, first, the landmark mapping process using artificial deformation is assessed. The source 3DCT is deformed artificially by non-linear matrices, which generated a ground truth to evaluate the resulting 3DCT. The iterative algorithm is appraised successfully with the artificial deformation approach. The second validation applies the landmark mapping and the volume morphing on real tumor data. Both the source and target 3DCTs are different phases of a lung 4DCT data. The statistical results, such as the min, max, and histogram of the density difference are summarized, which showed the resulting 3DCT is similar to the target 3DCT. The next step is to apply the whole algorithm to the unknown target 3DCT.
Conclusion: The iterative morphing algorithm is innovative and time saving. It has many potential applications in real-time image guided radiation treatment, such as online treatment error detection and intervention.
Funding Support, Disclosures, and Conflict of Interest: Industrail Support from PerkinElmer Inc, Varian Medical Research
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