Abstract
In this work, we present a viewpoint selection method specifically designed for fibrous structures in a pre-operative context. A view quality metric based on entropy was developed, which integrates the typical requirements of surgery planning. We applied our approach in the case of cranial nerves surrounding skull base tumors. The relevance of the viewpoints selected by our method was assessed qualitatively by a neurosurgeon and quantitatively based on statistical tests. These viewpoints were proven to have a high informative content, and therefore to enable a good understanding and mental representation the 3D anatomical scene in a pre-operative context.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Bonaventura, X., Feixas, M., Sbert, M., Chuang, L., Wallraven, C.: A survey of viewpoint selection methods for polygonal models. Entropy 20(5), 370 (2018)
Borkar, S.A., et al.: Prediction of facial nerve position in large vestibular schwannomas using diffusion tensor imaging tractography and its intraoperative correlation. Neurol. India 64(5), 965 (2016)
Chan, M.-Y., Qu, H., Wu, Y., Zhou, H.: Viewpoint selection for angiographic volume. In: Bebis, G., et al. (eds.) ISVC 2006. LNCS, vol. 4291, pp. 528–537. Springer, Heidelberg (2006). https://doi.org/10.1007/11919476_53
Chen, M., Feixas, M., Viola, I., Bardera, A., Shen, H.W., Sbert, M.: Information Theory Tools for Visualization. CRC Press (2016)
Jacquesson, T., et al.: Probabilistic tractography to predict the position of cranial nerves displaced by skull base tumors: value for surgical strategy through a case series of 62 patients. Neurosurgery 85(1), E125–E13 (2018)
Jacquesson, T., et al.: Overcoming challenges of cranial nerve tractography: a targeted review. Neurosurgery 84(2), 313–325 (2018)
Joo, W., Yoshioka, F., Funaki, T., Rhoton, A.L.: Microsurgical anatomy of the trigeminal nerve. Clin. Anat. 27, 61–88 (2014). https://doi.org/10.1002/ca.22330
Leopardi, P.: A partition of the unit sphere into regions of equal area and small diameter. Electron. Trans. Numer. Anal. 25, 309–327 (2006)
Mühler, K., Neugebauer, M., Tietjen, C., Preim, B.: Viewpoint selection for intervention planning. In: EuroVis, pp. 267–274 (2007)
Rhoton, A.L.: Microsurgical anatomy of the posterior fossa cranial nerves. Clin. Neurosurg. 26, 398–462 (1979)
Samii, M., Gerganov, V.M.: Petroclival meningiomas: quo vadis? World Neurosurg. 75(3–4), 424 (2011)
Smith, S.M., et al.: Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 23, S208–S219 (2004)
Song, F., et al.: In vivo visualization of the facial nerve in patients with acoustic neuroma using diffusion tensor imaging-based fiber tracking. J. Neurosurg. 125(4), 787–794 (2016)
Tournier, J.D., et al.: \(MRtrix3\): a fast, flexible and open software framework for medical image processing and visualisation. Neuroimage 202, 116137 (2019)
Xu, C., Prince, J.L.: Snakes, shapes, and gradient vector flow. IEEE Trans. Image Process. 7, 359–369 (1998)
Yoshino, M., et al.: Visualization of cranial nerves using high-definition fiber tractography. Neurosurgery 79, 146–165 (2016). https://doi.org/10.1227/NEU.0000000000001241
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 Springer Nature Switzerland AG
About this paper
Cite this paper
Decroocq, M., Ligneris, M.D., Jacquesson, T., Frindel, C. (2022). Viewpoint Selection for Fibrous Structures in a Pre-operative Context: Application to Cranial Nerves Surrounding Skull Base Tumors. In: Rozinaj, G., Vargic, R. (eds) Systems, Signals and Image Processing. IWSSIP 2021. Communications in Computer and Information Science, vol 1527. Springer, Cham. https://doi.org/10.1007/978-3-030-96878-6_5
Download citation
DOI: https://doi.org/10.1007/978-3-030-96878-6_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-96877-9
Online ISBN: 978-3-030-96878-6
eBook Packages: Computer ScienceComputer Science (R0)