Dr. Ching-Long Lin Profile

Dr. Ching-Long Lin

Professor at Univ of Iowa

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Proceedings Article | 27 February 2009 Paper

Local tissue-weight-based nonrigid registration of lung images with application to regional ventilation

Youbing Yin, Eric Hoffman, Ching-Long Lin

Proceedings Volume 7262, 72620C (2009) https://doi.org/10.1117/12.811715

KEYWORDS: Lung, Image registration, Tissues, Computed tomography, Virtual colonoscopy, Image segmentation, 3D modeling, Image resolution, Medical imaging, Optical flow

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In this paper, a new nonrigid image registration method is presented to align two volumetric lung CT datasets with an application to estimate regional ventilation. Instead of the sum of squared intensity difference (SSD), we introduce the sum of squared tissue volume difference (SSTVD) as the similarity criterion to take into account the variation of intensity due to respiration. This new criterion aims to minimize the local difference of tissue volume inside the lungs between two images scanned in the same session or over short periods of time, thus preserving the tissue weight of the lungs. Our approach is tested using a pair of volumetric lung datasets acquired at 15% and 85% of vital capacity (VC) in a single scanning session. The results show that the new SSTVD predicts a smaller registration error and also yields a better alignment of structures within the lungs than the normal SSD similarity measure. In addition, the regional ventilation derived from the new method exhibits a much more improved physiological pattern than that of SSD.

Proceedings Article | 14 April 2005 Paper

A numerical study of gas transport in human lung models

Ching-Long Lin, Eric Hoffman

Proceedings Volume 5746, (2005) https://doi.org/10.1117/12.601169

KEYWORDS: Xenon, Lung, Computed tomography, Binary data, Image segmentation, Gases, Helium, Magnetic resonance imaging, Systems modeling, Tomography

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Stable Xenon (Xe) gas has been used as an imaging agent for decades in its radioactive form, is chemically inert, and has been used as a ventilation tracer in its non radioactive form during computerized tomography (CT) imaging. Magnetic resonance imaging (MRI) using hyperpolarized Helium (He) gas and Xe has also emerged as a powerful tool to study regional lung structure and function. However, the present state of knowledge regarding intra-bronchial Xe and He transport properties is incomplete. As the use of these gases rapidly advances, it has become critically important to understand the nature of their transport properties and to, in the process, better understand the role of gas density in general in determining regional distribution of respiratory gases. In this paper, we applied the custom developed characteristic-Galerkin finite element method, which solves the three-dimensional (3D) incompressible variable-density Navier-Stokes equations, to study the transport of Xe and He in the CT-based human lung geometries, especially emulating the washin and washout processes. The realistic lung geometries are segmented and reconstructed from CT images as part of an effort to build a normative atlas (NIH HL-064368) documenting airway geometry over 4 decades of age in healthy and disease-state adult humans. The simulation results show that the gas transport process depends on the gas density and the body posture. The implications of these results on the difference between washin and washout time constants are discussed.

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