TY - GEN
T1 - Automated 3D segmentation of lung fields in thin slice CT exploiting wavelet preprocessing
AU - Korfiatis, P.
AU - Skiadopoulos, S.
AU - Sakellaropoulos, P.
AU - Kalogeropoulou, C.
AU - Costaridou, L.
PY - 2007
Y1 - 2007
N2 - 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.
AB - 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.
KW - Adaptive wavelet edge enhancement
KW - Automated 3D thresholding
KW - Computerized CT lung analysis
KW - Lung volume segmentation
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U2 - 10.1007/978-3-540-74272-2_30
DO - 10.1007/978-3-540-74272-2_30
M3 - Conference contribution
AN - SCOPUS:38149078813
SN - 9783540742715
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 237
EP - 244
BT - Computer Analysis of Images and Patterns - 12th International Conference, CAIP 2007, Proceedings
PB - Springer Verlag
T2 - 12th International Conference on Computer Analysis of Images and Patterns, CAIP 2007
Y2 - 27 August 2007 through 29 August 2007
ER -