Abstract
Needle insertion planning for breast biopsy has the potential to improve patient comfort and intervention safety. However, this is a challenging task because of the infinite possibilities of insertion points and the breast tissue deformations during the procedure. In this paper, we present a novel approach that couples probabilistic motion planning methods with Finite Element Simulation in order to find an optimal path taking breast deformation into account. This method reduces the error (i.e. the distance between the needle tip and the lesion) meanly by 80% and the proposed planner divides the planning time by 5 in comparison to a classic Rapidly-Exploring Random Tree planning method.
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References
Deurloo, E., Gilhuijs, K., Kool, L., Müller, S.: Displacement of breast tissue and needle deviation during stereotactic procedures. Investigative Radiology 36 (2001)
Genaro, G., Baldan, E., Bezzon, E., La Grassa, M., et al.: Clinical Performance of Digital Breast Tomosynthesis Versus Full-Field Digital Mammography: Preliminary Results. In: Krupinski, E.A. (ed.) IWDM 2008. LNCS, vol. 5116, pp. 477–482. Springer, Heidelberg (2008)
Alterovitz, R., Goldberg, K., Okamura, A.: Planning for Steerable Bevel-tip Needle Insertion Through 2D Soft Tissue with Obstacles. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 1652–1657 (2005)
DiMaio, S.P., Salcudean, S.E.: Needle Steering and Motion Planning in Soft Tissues. IEEE Transactions on Biomedical Engineering (2004)
Hauser, K., Alterovitz, R., Chentanez, N., Okamura, A., Goldberg, K.: Feedback Control for Steering Needles Through 3D Deformable Tissue Using Helical Paths. Robotics: Science and Systems V (2009)
Dehghan, E., Salcudean, S.E.: Needle Insertion Parameter Optimization for Brachytherapy. IEEE Trans. on Robotics 25, 303–315 (2009)
Latombe, J.-C.: Robot Motion Planning. Kluwer Academic Publishers, Boston (1991)
Gibson, S.F.F., Mirtich, B.: A survey of Deformable Modeling in Computer Graphics., TR-97-19, Mitsubishi Electric Research Laboratory (1997)
Schroeder, W.J., Avila, L.S., Hoffman, W.: Visualizing with VTK: a tutorial. IEEE Computer Graphics and Applications 20, 20–27 (2000)
Vancamberg, L., Sahbani, A., Muller, S., Morel, G.: Needle Path Planning for Digital Breast Tomosynthesis Biopsy. In: IEEE International Conference on Robotics and Automation, ICRA (2010)
LaValle, S.M.: Rapidly-Exploring Random Trees: A New Tool for Path Planning, TR 98-11, Department of Computer Science, Iowa State University (1998)
Xu, J., Duindam, V., Alterovitz, R., Goldberg, K.: Motion Planning for Steerable Needles in 3D Environments with Obstacles Using Rapidly-Exploring Random Trees and Backchaining. In: IEEE International Conference on Automation Science and Engineering (2008)
Webster III, R.J., Cowan, N.J., Chirikjian, G., Okamura, A.M.: Nonholonomic Modeling of Needle Steering. In: 9th International Symposium on Experimental Robotics (2004)
Nienhuys, H.W., van der Stappen, A.F.: A computational technique for interactive needle insertions in 3D nonlinear material. In: IEEE International Conference on Robotics and Automation, ICRA (2004)
Krouskop, T.A., Wheeler, T.M., Kallel, F., Garra, B.S., Hall, T.: Elastic Moduli of Breast and Prostate Tissues Under Compression. Ultrasonic Imaging 20, 260–278 (1998)
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Vancamberg, L., Sahbani, A., Muller, S., Morel, G. (2010). Needle Path Planning Method for Digital Breast Tomosynthesis Biopsy Based on Probabilistic Techniques. In: Martí, J., Oliver, A., Freixenet, J., Martí, R. (eds) Digital Mammography. IWDM 2010. Lecture Notes in Computer Science, vol 6136. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13666-5_3
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DOI: https://doi.org/10.1007/978-3-642-13666-5_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13665-8
Online ISBN: 978-3-642-13666-5
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