Publication | Open Access
Liver Vessels Segmentation Using a Hybrid Geometrical Moments/Graph Cuts Method
75
Citations
20
References
2009
Year
Image ReconstructionEngineeringComputer-aided DesignBiomedical EngineeringDiagnostic ImagingImage AnalysisCylindrical ShapesComputational GeometryLiver Vessel SegmentationComputational AnatomyRadiologyHealth SciencesGeometric ModelingMachine VisionVascular ImageMedical ImagingMedical Image ComputingComputer VisionHepatologyGraph Cuts AlgorithmLiver Vessels SegmentationBiomedical ImagingComputer-aided DiagnosisMedical Image AnalysisImage Segmentation
This paper describes a fast and fully automatic method for liver vessel segmentation on computerized tomography scan preoperative images. The basis of this method is the introduction of a 3-D geometrical moment-based detector of cylindrical shapes within the minimum-cut/maximum-flow energy minimization framework. This method represents an original way to introduce a data term as a constraint into the widely used Boykov's graph cuts algorithm, and hence, to automate the segmentation. The method is evaluated and compared with others on a synthetic dataset. Finally, the relevancy of our method regarding the planning of a necessarily accurate percutaneous high-intensity focused ultrasound surgical operation is demonstrated with some examples.
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