Iterative mesh transformation for 3D segmentation of livers with cancers in CT images

Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society
Difei LuWenli Cai

Abstract

Segmentation of diseased liver remains a challenging task in clinical applications due to the high inter-patient variability in liver shapes, sizes and pathologies caused by cancers or other liver diseases. In this paper, we present a multi-resolution mesh segmentation algorithm for 3D segmentation of livers, called iterative mesh transformation that deforms the mesh of a region-of-interest (ROI) in a progressive manner by iterations between mesh transformation and contour optimization. Mesh transformation deforms the 3D mesh based on the deformation transfer model that searches the optimal mesh based on the affine transformation subjected to a set of constraints of targeting vertices. Besides, contour optimization searches the optimal transversal contours of the ROI by applying the dynamic-programming algorithm to the intersection polylines of the 3D mesh on 2D transversal image planes. The initial constraint set for mesh transformation can be defined by a very small number of targeting vertices, namely landmarks, and progressively updated by adding the targeting vertices selected from the optimal transversal contours calculated in contour optimization. This iterative 3D mesh transformation constrained by 2D optimal transversa...Continue Reading

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Citations

Nov 10, 2015·Computers in Biology and Medicine·Chunhua DongHuiyan Jiang
Apr 30, 2016·Computational and Mathematical Methods in Medicine·Weiwei WuYanhua Zhang
Jun 20, 2018·Journal of Digital Imaging·L E CarvalhoA von Wangenheim
Dec 5, 2017·Journal of Healthcare Engineering·Chunhua DongYen-Wei Chen

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