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Lung Parenchyma Segmentation from CT Images Based on Material Decomposition

  • Carlos Vinhais
  • Aurélio Campilho
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4142)

Abstract

We present a fully automated method for extracting the lung region from volumetric X-ray CT images based on material decomposition. By modeling the human thorax as a composition of different materials, the proposed method follows a threshold-based, hierarchical voxel classification strategy. The segmentation procedure involves the automatic computation of threshold values and consists on three main steps: patient segmentation and decomposition, large airways extraction and lung parenchyma decomposition, and lung region of interest segmentation. Experimental results were performed on thoracic CT images acquired from 30 patients. The method provides a reproducible set of thresholds for accurate extraction of the lung parenchyma, needed for computer aided diagnosis systems.

Keywords

Compute Tomography Image Lung Parenchyma Lung Region Compute Tomography Number Large Airway 
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

  • Carlos Vinhais
    • 1
    • 2
  • Aurélio Campilho
    • 1
    • 3
  1. 1.INEB – Instituto de Engenharia Biomédica, Laboratório de Sinal e Imagem BiomédicaPortoPortugal
  2. 2.ISEP – Instituto Superior de Engenharia do PortoDepartamento de FísicaPortoPortugal
  3. 3.Faculdade de Engenharia, Departamento de Engenharia Electrotécnica e ComputadoresUniversidade do PortoPortoPortugal

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