Automatic Left and Right Lung Separation Using Free-formed Surface Fitting on Volumetric CT

Youn Joo Lee, Minho Lee, Namkug Kim, Joon Beom Seo, Joo Young Park
Journal of Digital Imaging, August 2014
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This study introduces a fully automated method for accurately separating the left and right lungs using volumetric computed tomography (CT) scans. The method utilizes free-formed surface fitting and iterative 3-dimensional morphological operators to divide the lungs. A separating surface is determined by detecting a point set that traverses between the initial left and right lungs, and a free-formed surface-fitting algorithm models the separating surface. The left and right lung volumes are then separated using this surface. The performance of the automated method was evaluated against manual segmentation by a human expert using 44 CT examinations. The results demonstrated high accuracy, with small surface distances and volumetric overlap errors between the automatic and manual methods. The study validates the feasibility of automatically separating the left and right lungs through the identification of a continuous 3D separating surface in volumetric chest CT images. The proposed method has been implemented in the AVIEW Lobe Segmentation page.


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