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Paper
21 March 2016 Improved B-spline image registration between exhale and inhale lung CT images based on intensity and gradient orientation information
Woo Hyun Nam, Jihun Oh, Jonghyon Yi, Yongsup Park, Hansu Cho, Sukjin Kim
Author Affiliations +
Abstract
Registration of lung CT images acquired at different respiratory phases is clinically relevant in many applications, such as follow-up analysis, lung function analysis based on mechanical elasticity, or pulmonary airflow analysis, etc. In order to find accurate and reliable transformation for registration, a proper choice of dissimilarity measure is important. Even though various intensity-based measures have been introduced for precise registration, the registration performance may be limited since they mainly take intensity values into account without effectively considering useful spatial information. In this paper, we attempt to improve the non-rigid registration accuracy between exhale and inhale CT images of the lung, by proposing a new dissimilarity measure based on gradient orientation representing the spatial information in addition to vessel-weighted intensity and normalized intensity information. Since it is necessary to develop non-rigid registration that can account for large lung deformations, the B-spline free-form deformation (FFD) is adopted as the transformation model. The experimental tests for six clinical datasets show that the proposed method provides more accurate registration results than competitive registration methods.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Woo Hyun Nam, Jihun Oh, Jonghyon Yi, Yongsup Park, Hansu Cho, and Sukjin Kim "Improved B-spline image registration between exhale and inhale lung CT images based on intensity and gradient orientation information", Proc. SPIE 9784, Medical Imaging 2016: Image Processing, 978440 (21 March 2016); https://doi.org/10.1117/12.2217390
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Cited by 1 scholarly publication.
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KEYWORDS
Image registration

Lung

Computed tomography

Image restoration

Image segmentation

Optimization (mathematics)

Electronics

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