Estimation of lung lobar sliding using image registration

Ryan Amelon; Kunlin Cao; Joseph M. Reinhardt; Gary E. Christensen; Madhavan Raghavan

doi:10.1117/12.911614

16 April 2012 Estimation of lung lobar sliding using image registration

Ryan Amelon, Kunlin Cao, Joseph M. Reinhardt, Gary E. Christensen, Madhavan Raghavan

Author Affiliations +

Proceedings Volume 8317, Medical Imaging 2012: Biomedical Applications in Molecular, Structural, and Functional Imaging; 83171H (2012) https://doi.org/10.1117/12.911614
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

MOTIVATION: The lobes of the lungs slide relative to each other during breathing. Quantifying lobar sliding can aid in better understanding lung function, better modeling of lung dynamics, and a better understanding of the limits of image registration performance near fissures. We have developed a method to estimate lobar sliding in the lung from image registration of CT scans. METHODS: Six human lungs were analyzed using CT scans spanning functional residual capacity (FRC) to total lung capacity (TLC). The lung lobes were segmented and registered on a lobe-by-lobe basis. The displacement fields from the independent lobe registrations were then combined into a single image. This technique allows for displacement discontinuity at lobar boundaries. The displacement field was then analyzed as a continuum by forming finite elements from the voxel grid of the FRC image. Elements at a discontinuity will appear to have undergone significantly elevated 'shear stretch' compared to those within the parenchyma. Shear stretch is shown to be a good measure of sliding magnitude in this context. RESULTS: The sliding map clearly delineated the fissures of the lung. The fissure between the right upper and right lower lobes showed the greatest sliding in all subjects while the fissure between the right upper and right middle lobe showed the least sliding.

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Ryan Amelon, Kunlin Cao, Joseph M. Reinhardt, Gary E. Christensen, and Madhavan Raghavan "Estimation of lung lobar sliding using image registration", Proc. SPIE 8317, Medical Imaging 2012: Biomedical Applications in Molecular, Structural, and Functional Imaging, 83171H (16 April 2012); https://doi.org/10.1117/12.911614

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