Liver segment approximation in CT data for surgical resection planning

• DOI: 10.1117/12.535514
• Publication Date: 2004-06-17T13:28:58Z
• Authors: Reinhard Beichel; Thomas Pock; Christian Janko; Roman B. Zotter; Bernhard Reitinger; Alexander Bornik; Kalman Palagyi; Erich Sorantin; Georg Werkgartner; Horst Bischof; Milan Sonka
• Keywords: Surgical Planning; Tree (set theory); Line segment

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