Automated 3D segmentation of lung fields in thin slice CT exploiting wavelet preprocessing

P. Korfiatis, S. Skiadopoulos, P. Sakellaropoulos, C. Kalogeropoulou, L. Costaridou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationComputer Analysis of Images and Patterns - 12th International Conference, CAIP 2007, Proceedings
Pages237-244
Number of pages8
StatePublished - Dec 1 2007
Event12th International Conference on Computer Analysis of Images and Patterns, CAIP 2007 - Vienna, Austria
Duration: Aug 27 2007Aug 29 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4673 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Conference on Computer Analysis of Images and Patterns, CAIP 2007
CountryAustria
CityVienna
Period8/27/078/29/07

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Keywords

  • Adaptive wavelet edge enhancement
  • Automated 3D thresholding
  • Computerized CT lung analysis
  • Lung volume segmentation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Korfiatis, P., Skiadopoulos, S., Sakellaropoulos, P., Kalogeropoulou, C., & Costaridou, L. (2007). Automated 3D segmentation of lung fields in thin slice CT exploiting wavelet preprocessing. In Computer Analysis of Images and Patterns - 12th International Conference, CAIP 2007, Proceedings (pp. 237-244). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4673 LNCS).