Abstract
Visualizing physical phenomena is a central tool for nowadays research. In particular, volumetric representations are a critical factor in the diagnosis of diseases and surgery planning. In the last years, rendering techniques have been essential for medical practice, but these approaches are suitable for representing non-rigid motion in tissue and internal organs. In the present chapter, we introduce a mapping algorithm capable of track non-rigid deformations on free-form objects. The proposed method uses k-means for partition algorithm and covariance ellipsoid, afterward the Germinal Center Optimization is used to adapt the ellipsoid parameters. We offer experimental results over the Stanford Repository and tumors.
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Villaseñor, C., Arana-Daniel, N., Alanis, A.Y., Lopez-Franco, C., Valencia-Murillo, R. (2020). Tracking of Non-rigid Motion in 3D Medical Imaging with Ellipsoidal Mapping and Germinal Center Optimization. In: Castillo, O., Melin, P. (eds) Hybrid Intelligent Systems in Control, Pattern Recognition and Medicine. Studies in Computational Intelligence, vol 827. Springer, Cham. https://doi.org/10.1007/978-3-030-34135-0_17
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DOI: https://doi.org/10.1007/978-3-030-34135-0_17
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