Paper
28 May 2001 Modeling liver motion and deformation during the respiratory cycle using intensity-based free-form registration of gated MR images
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Abstract
In this paper, we demonstrate a technique for modeling liver motion during the respiratory cycle using intensity-based free-form deformation registration of gated MR images. We acquired 3D MR image sets (multislice 2D) of the abdomen of four volunteers at end-inhalation, end-exhalation, and eight time points in between using respiratory gating. We computed the deformation field between the images using intensity-based rigid and non-rigid registration algorithms. The non-rigid transformation is a free-form deformation with B-spline interpolation between uniformly-spaced control points. The transformations between inhalation and exhalation were visually inspected. Much of the liver motion is cranial-caudal translation, and thus the rigid transformation captures much of the motion. However, there is still substantial residual deformation of up to 2 cm. The free-form deformation produces a motion field that appears on visual inspection to be accurate. This is true for the liver surface, internal liver structures such as the vascular tree, and the external skin surface. We conclude that abdominal organ motion due to respiration can be satisfactorily modeled using an intensity-based non-rigid 4D image registration approach. This allows for an easier and potentially more accurate and patient-specific deformation field computation than physics-based models using assumed tissue properties and acting forces.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Torsten Rohlfing, Calvin R. Maurer Jr., Walter G. O'Dell, and Jianhui Zhong "Modeling liver motion and deformation during the respiratory cycle using intensity-based free-form registration of gated MR images", Proc. SPIE 4319, Medical Imaging 2001: Visualization, Display, and Image-Guided Procedures, (28 May 2001); https://doi.org/10.1117/12.428073
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Cited by 70 scholarly publications and 1 patent.
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KEYWORDS
Image registration

Liver

Motion models

Magnetic resonance imaging

Image fusion

Rigid registration

Visualization

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