Automated 3D Segmentation of Lung Fields in Thin Slice CT Exploiting Wavelet Preprocessing

  • Panayiotis Korfiatis
  • Spyros Skiadopoulos
  • Philippos Sakellaropoulos
  • Christina Kalogeropoulou
  • Lena Costaridou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4673)


Lung segmentation is a necessary first step to computer analysis in lung CT. It is crucial to develop automated segmentation algorithms capable of dealing with the amount of data produced in thin slice multidetector CT and also to produce accurate border delineation in cases of high density pathologies affecting the lung border. In this study an automated method for lung segmentation of thin slice CT data is proposed. The method exploits the advantage of a wavelet preprocessing step in combination with the minimum error thresholding technique applied on volume histogram. Performance averaged over left and right lung volumes is in terms of: lung volume overlap 0.983 ± 0.008, mean distance 0.770 ± 0.251 mm, rms distance 0.520 ± 0.008 mm and maximum distance differentiation 3.327 ± 1.637 mm. Results demonstrate an accurate method that could be used as a first step in computer lung analysis in CT.


lung volume segmentation automated 3D thresholding adaptive wavelet edge enhancement computerized CT lung analysis 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Panayiotis Korfiatis
    • 1
  • Spyros Skiadopoulos
    • 1
  • Philippos Sakellaropoulos
    • 1
  • Christina Kalogeropoulou
    • 2
  • Lena Costaridou
    • 1
  1. 1.Department of Medical Physics, School of Medicine, University of Patras, 265 00 PatrasGreece
  2. 2.Department of Radiology, School of Medicine, University of Patras, 265 00 PatrasGreece

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