Identify the centerline of tubular structure in medical images
Author(s) -
Yu-Tai Ching,
Carlos Yeh
Publication year - 2005
Publication title -
proceedings of spie, the international society for optical engineering/proceedings of spie
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
eISSN - 1996-756X
pISSN - 0277-786X
DOI - 10.1117/12.595318
Subject(s) - hessian matrix , pixel , artificial intelligence , computer science , scale (ratio) , path (computing) , matrix (chemical analysis) , computer vision , image segmentation , line segment , graph , image (mathematics) , pattern recognition (psychology) , mathematics , algorithm , physics , theoretical computer science , materials science , quantum mechanics , composite material , programming language
Finding the centerline of the tubular structure helps to segment or analyze the organs such as the vessels or neuron fibers in medical images. This paper described a semi-automatic method using the minimum cost path finding and Hessian matrix analysis in scale space to calculate the centerline of tubular structure organs. Unlike previous approaches, exhaustive search for line-like shapes in every scale is prevent. Centerline pixels candidates and the width of the vessel are extracted by analyzing the intensity profile along the gradient vectors in the image. A verification procedure using Hassian matrix analysis with the scale obtained from the gradient analysis is applied to those candidates. Results obtained from the Hessian matrix analysis are used to construct a weighted graph. Finding the minimum cost path in the graph gives the centerline of the tubular structure. The method is applied to find the centerline of the vessels in the 2D angiogram and the neuron fibers in the 3D confocal microscopic images.
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