A Thinning-based Liver Vessel Skeletonization Method

Abstract

In the clinical practice of diagnosis and treatment of liver disease, how to effectively represent and analyze the vascular structure has been a widely studied topic for a long time. In this paper, we propose a method for the threedimensional skeletal graph generation of liver vessels using 3D thinning algorithm and graph theory. First of all, the principal methods for skeletonization are introduced, followed by their comparative analysis. Secondly, the 3D thinning-based skeletonization method together with a filling hole pre-processing on liver vessel image are employed to form the liver skeleton. A graph-based technique is then employed on the skeleton image to efficiently form the liver vascular graph. The thinning-based liver vessel skeletonization method was evaluated on liver vessel images with other two kinds of skeletonization approaches to show its effectiveness and efficiency.

VIPAR, a quantitative approach to 3D histopathology applied to lymphatic malformations

“…Connected component analysis (41) was applied to both segmentations in order to identify and remove artifacts in the form of small voxel components in both foreground (spurious objects) and background (cavities). Skeletonization computed the medial axis within each vessel, applying the voxel-thinning method proposed by Chen et al (32). We modified the algorithm in order to reduce the number of spurious branches when iterating on vessels reduced to thin sheets of voxels.…”

“…Blood vessels were segmented semiautomatically by computing Hessian vesselness features on multiple Gaussian scales (31), followed by manual global thresholding to obtain a binary image and postprocessing to remove small segmentation artefacts. The segmented vessel structures were represented as binary volume ( Figure 5, D-F), and, for subsequent skeletonization, the medial axis within each vessel was computed using the voxel-thinning method ( Figure 5, G-I) (32). The topology of the resulting vessel network was extracted by identification of branching points and skeleton voxels that belong to vessel segments based on the definitions of Klette (33).…”

Estudo e desenvolvimento de algoritmos de esqueletização com aplicação em redes vasculares ósseas

“…Essa é uma medida muito comum e que inclusive é um requisito que faz parte da definição de esqueleto. Ela sugere que os esqueletos devem estar situados no centro de seus respectivos objetos (CHEN et al, 2011), o mais próximo do eixo médio (SHE et al, 2009) e o mais distante possível da borda dos mesmos (DUNCAN;GERIG, 2005). Em aplicações como estimação de caminho para a realização de endoscopia essa característica é muito importante para evitar perfuração dos órgãos (WAN et al, 2002), até mesmo na endoscopia virtual, pois se a câmera virtual estiver bem centrada ela fornecerá uma visão mais ampla do ambiente virtual (WAN; DACHILLE; KAUFMAN, 2001).…”

“…Essa medida garante que o esqueleto deve ter a espessura de um voxel, ou seja, ele deve ser fino (CHEN et al, 2011) e não deve conter nenhuma estrutura bidimensional (WAN; DACHILLE; KAUFMAN, 2001).…”

“…O esqueleto deve ser insensível a pequenas perturbações, ou ruídos, na superfície do objeto (CHEN et al, 2011). Essa característica é necessária em praticamente todas as aplicações, pois quase todos os dados de entrada biológicos tem algum nível de ruído.…”