Liver segment approximation in CT data for surgical resection planning

Reinhard Beichel; Thomas Pock; Christian Janko; Roman B. Zotter; Bernhard Reitinger; Alexander Bornik; Kalman Palagyi; Erich Sorantin; Georg Werkgartner; Horst Bischof; Milan Sonka

doi:10.1117/12.535514

12 May 2004 Liver segment approximation in CT data for surgical resection planning

Reinhard Beichel, Thomas Pock, Christian Janko, Roman B. Zotter, Bernhard Reitinger, Alexander Bornik, Kalman Palagyi, Erich Sorantin, Georg Werkgartner, Horst Bischof, Milan Sonka

Author Affiliations +

Proceedings Volume 5370, Medical Imaging 2004: Image Processing; (2004) https://doi.org/10.1117/12.535514
Event: Medical Imaging 2004, 2004, San Diego, California, United States

Abstract

Surgical planning of liver tumor resections requires detailed three-dimensional (3D) understanding of the complex arrangement of vasculature, liver segments and tumors. Knowledge about location and sizes of liver segments is important for choosing an optimal surgical resection approach and predicting postoperative residual liver capacity. The aim of this work is to facilitate such surgical planning process by developing a robust method for portal vein tree segmentation. The work also investigates the impact of vessel segmentation on the approximation of liver segment volumes. For segment approximation, smaller portal vein branches are of importance. Small branches, however, are difficult to segment due to noise and partial volume effects. Our vessel segmentation is based on the original gray-values and on the result of a vessel enhancement filter. Validation of the developed portal vein segmentation method in computer generated phantoms shows that, compared to a conventional approach, more vessel branches can be segmented. Experiments with in vivo acquired liver CT data sets confirmed this result. The outcome of a Nearest Neighbor liver segment approximation method applied to phantom data demonstrates, that the proposed vessel segmentation approach translates into a more accurate segment partitioning.

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Reinhard Beichel, Thomas Pock, Christian Janko, Roman B. Zotter, Bernhard Reitinger, Alexander Bornik, Kalman Palagyi, Erich Sorantin, Georg Werkgartner, Horst Bischof, and Milan Sonka "Liver segment approximation in CT data for surgical resection planning", Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004); https://doi.org/10.1117/12.535514

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