Mr. Se-Young Chun Profile

Se-Young Chun

at Univ of Michigan

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Proceedings Article | 27 March 2009 Paper

A simple penalty that encourages local invertibility and considers sliding effects for respiratory motion

Se Young Chun, Jeffrey Fessler, Marc Kessler

Proceedings Volume 7259, 72592U (2009) https://doi.org/10.1117/12.811181

KEYWORDS: Bone, Image registration, Tissues, 3D image processing, Image resolution, Medical imaging, Motion estimation, Computed tomography, Selenium, Transform theory

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Nonrigid image registration is a key tool in medical imaging. Because of high degrees of freedom in nonrigid transforms, there have been many efforts to regularize the deformation based on some reasonable assumptions. Especially, motion invertibility and local tissue rigidity have been investigated as reasonable priors in image registration. There have been several papers on exploiting each constraint separately. These constraints are reasonable in respiratory motion estimation because breathing motion is invertible and there are some rigid structures such as bones. Using both constraints seems very attractive in respiratory motion registration since using invertibility prior alone usually causes bone warping in ribs. Using rigidity prior seems natural and straightforward. However, the "sliding effect" near the interface between rib cage and diaphragm makes problem harder because it is not locally invertible. In this area, invertibility and rigidity priors have opposite forces. Recently, we proposed a simple piecewise quadratic penalty that encourages the local invertibility of motions. In this work we relax this penalty function by using a Geman-type function that allows the deformation to be piecewise smooth instead of globally smooth. This allows the deformation to be discontinuous in the area of the interface between rib cage and diaphragm. With some small sacrifice of regularity, we could achieve more realistic discontinuous motion near diaphragm, better data fitting error as well as less bone warping. We applied this Geman-type function penalty only to the x- and y-direction partial derivatives of the z-direction deformation to address the sliding effect. 192 × 128 × 128 3D CT inhale and exhale images of a real patient were used to show the benefits of this new penalty method.

Proceedings Article | 13 March 2009 Paper

Joint image reconstruction and nonrigid motion estimation with a simple penalty that encourages local invertibility

Se Young Chun, Jeffrey Fessler

Proceedings Volume 7258, 72580U (2009) https://doi.org/10.1117/12.811067

KEYWORDS: Image restoration, Motion estimation, Motion models, Spatial resolution, Image registration, Positron emission tomography, Medical imaging, Image quality, Computed tomography, Signal to noise ratio

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Motion artifacts are a significant issue in medical image reconstruction. There are many methods for incorporating motion information into image reconstruction. However, there are fewer studies that focus on deformation regularization in motioncompensated image reconstruction. The usual choice for deformation regularization has been penalty functions based on the assumption that tissues are elastic. In the image registration field, there have been some methods proposed that impose deformation invertibility using constraints or regularization, assuming that organ motions are invertible transformations. However, most of these methods require very high memory or computation complexity, making them poorly suited for dealing with multiple images simultaneously in motion-compensated image reconstruction. Recently we proposed an image registration method that uses a simple penalty function based on a sufficient condition for the local invertibility of deformations.¹ That approach encourages local invertibility in a fast and memory-efficient way. This paper investigates the use of that regularization method for the more challenging problem of joint image reconstruction and nonrigid motion estimation. A 2D PET simulation (based on realistic motion from real patient CT data) demonstrates the benefits of such motion regularization for joint image reconstruction/registration.

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