Abstract
Article presents methodology of computer aided destroying focal liver lesions using imaging navigation system. Methodology allows generation of personalized anatomical model of patient’s liver based on CAT screening with contract media of abdominal cavity, registration of edited anatomical model relative to real patient’s position on operation block, presentation of surgical tools position during treatment on the liver’s anatomical model and non-direct monitoring of ablation process of lesions. Liver anatomy model comprises organ’s and focal lesions’ surface and central lines of vascular structures in liver. Generation of personalized patient’s model has been verified based on anonymized abdominal cavity CAT with contrast media screening cases. The registration methodology has been evaluated on imaging data and patient from the Second Department of Clinical Radiology and the Chair and Department of General, Transplant and Liver Surgery at the Medical University of Warsaw after acceptance of the ethics committee of the Medical University of Warsaw.
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
Preview
Unable to display preview. Download preview PDF.
References
Pereira, P.: Actual role of radiofrequency ablation of liver metastases. Eur. Radiol. 17, 2062–2070 (2007)
Spinczyk, D., Karwan, A., Rudnicki, J., Wróblewski, T.: Stereoscopic liver surface reconstruction. Videosurgery and Other Miniinvasive Techniques 7, 181–187 (2012)
Spinczyk, D., Karwan, A., et al.: In vitro evaluation of stereoscopic liver surface reconstruction. Videosurgery and Other Miniinvasive Techniques 8, 80–85 (2013)
Phee, S., Yang, K.: Interventional navigation systems for treatment of unresectable liver tumor. Medical & Biological Engineering and Computing 48, 103–111 (2010)
Peters, T., Cleary, K.: Image-Guided Interventions: Technology and Applications. Springer (2008)
Juszczyk, J.: Sekwencyjna segmentacja wybranych struktur anatomicznych w serii obrazów tomograficznych. PhD thesis. Silesian University of Technology (2012)
Frangi, A.F., Niessen, W.J., Vincken, K.L., Viergever, M.A.: Multiscale Vessel enhancement Filtering. In: Wells, W.M., Colchester, A.C.F., Delp, S.L. (eds.) MICCAI 1998. LNCS, vol. 1496, pp. 130–137. Springer, Heidelberg (1998)
Rudzki, M.: Filtr wieloskalowy w detekcji struktur naczyniowych wątroby z obrazów tomografii komputerowej. PhD thesis. Silesian University of Technology (2011)
Xing, Z., Jie, T., Dehui, X., Xiuli, L., Kexin, D.: Interactive liver tumor segmentation from ct scans using support vector classification with watershed. In: Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC, vol. 3, pp. 6005–6008 (2011)
Häme, Y.: Liver Tumor Segmentation Using Implicit Surface Evolution. The Midas Journal (2008)
Badura, P., Pietka, E.: 3D Fuzzy Liver Tumor Segmentation. In: Piętka, E., Kawa, J. (eds.) ITIB 2012. LNCS, vol. 7339, pp. 47–57. Springer, Heidelberg (2012)
Spinczyk, D.: System nawigacji obrazowej w ablacji zmian ogniskowych w wątrobie. Silesian University of Technology (2013)
Horn, B., Hilden, H., Negahdaripour, S.: Closed form solution of absolute orientation using orthonormal matrices. J. Opt. Soc. Am. A 5, 1127–1135 (1988)
Fitzpatrick, J., West, J., Mauer, C.: Predicting error in rigid-body point-based registration. IEEE Trans. Med. Imaging. 17, 694–702 (1988)
Spinczyk, D., Zylkowski, J., Wróblewski, T.: Continuous registration based on computed tomography for breathing motion compensation. Videosurgery and Other Miniinvasive Techniques 8, 265–272 (2013)
Seitel, A., Maier-Hein, L., Schawo, S., Radeleff, B., Mueller, S., Pianka, F., Schmied, B., Meinzer, H.: In-vitro evaluation of different visualization approaches for computer assisted targeting in soft tissue. Computer-Assisted Radiology and Surgery 2(suppl. 1), S188–S190 (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Spinczyk, D. (2014). Assistance in Destroying Focal Lesions in the Liver Using Image Navigation. In: Piętka, E., Kawa, J., Wieclawek, W. (eds) Information Technologies in Biomedicine, Volume 4. Advances in Intelligent Systems and Computing, vol 284. Springer, Cham. https://doi.org/10.1007/978-3-319-06596-0_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-06596-0_2
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-06595-3
Online ISBN: 978-3-319-06596-0
eBook Packages: EngineeringEngineering (R0)