Accurate Banded Graph Cut Segmentation of Thin Structures Using Laplacian Pyramids

  • Ali Kemal Sinop
  • Leo Grady
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4191)


The Graph Cuts method of interactive segmentation has become very popular in recent years. This method performs at interactive speeds for smaller images/volumes, but an unacceptable amount of storage and computation time is required for the large images/volumes common in medical applications. The Banded Graph Cut (BGC) algorithm was proposed to drastically increase the computational speed of Graph Cuts, but is limited to the segmentation of large, roundish objects. In this paper, we propose a modification of BGC that uses the information from a Laplacian pyramid to include thin structures into the band. Therefore, we retain the computational efficiency of BGC while providing quality segmentations on thin structures. We make quantitative and qualitative comparisons with BGC on images containing thin objects. Additionally, we show that the new parameter introduced in our modification provides a smooth transition from BGC to traditional Graph Guts.


Coarse Level Subtraction Image Thin Structure Segmentation Task Laplacian Pyramid 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ali Kemal Sinop
    • 1
  • Leo Grady
    • 1
  1. 1.Department of Imaging and VisualizationSiemens Corporate ResearchPrincetonUSA

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