title: Segmentation of hepatic vessels from MRI images for planning of electroporation-based treatments in the liver.
abstract: BACKGROUND
  Electroporation-based treatments rely on increasing the permeability of the cell membrane by high voltage electric pulses delivered to tissue via electrodes. To ensure that the whole tumor is covered by the sufficiently high electric field, accurate numerical models are built based on individual patient geometry. For the purpose of reconstruction of hepatic vessels from MRI images we searched for an optimal segmentation method that would meet the following initial criteria: identify major hepatic vessels, be robust and work with minimal user input.
  
  
  METHODS
  We tested the approaches based on vessel enhancement filtering, thresholding, and their combination in local thresholding. The methods were evaluated on a phantom and clinical data.
  
  
  RESULTS
  Results show that thresholding based on variance minimization provides less error than the one based on entropy maximization. Best results were achieved by performing local thresholding of the original de-biased image in the regions of interest which were determined through previous vessel-enhancement filtering. In evaluation on clinical cases the proposed method scored in average sensitivity of 93.68%, average symmetric surface distance of 0.89 mm and Hausdorff distance of 4.04 mm.
  
  
  CONCLUSIONS
  The proposed method to segment hepatic vessels from MRI images based on local thresholding meets all the initial criteria set at the beginning of the study and necessary to be used in treatment planning of electroporation-based treatments: it identifies the major vessels, provides results with consistent accuracy and works completely automatically. Whether the achieved accuracy is acceptable or not for treatment planning models remains to be verified through numerical modeling of effects of the segmentation error on the distribution of the electric field.
authors.affiliation: University of Ljubljana, Faculty of Electrical Engineering, Ljubljana, Slovenia.
authors.forename: Marija
authors.initials: M
authors.lastname: Marcan
authors.affiliation: University of Ljubljana, Faculty of Electrical Engineering, Ljubljana, Slovenia.
authors.forename: Denis
authors.initials: D
authors.lastname: Pavliha
authors.affiliation: Institute of Oncology Ljubljana, Ljubljana, Slovenia.
authors.forename: Maja Marolt
authors.initials: MM
authors.lastname: Music
authors.affiliation: Clinical Department for Diagnostic and Interventional Radiology, Clinical Hospital "Dubrava", Zagreb, Croatia.
authors.forename: Igor
authors.initials: I
authors.lastname: Fuckan
authors.affiliation: University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, Croatia.
authors.forename: Ratko
authors.initials: R
authors.lastname: Magjarevic
authors.affiliation: University of Ljubljana, Faculty of Electrical Engineering, Ljubljana, Slovenia.
authors.forename: Damijan
authors.initials: D
authors.lastname: Miklavcic
keywords: MRI of liver; electrochemotherapy; hepatic vessel segmentation; non-invasive tumor treatments; non-thermal irreversible electroporation; treatment planning