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Proceedings Paper

Accurate registration of temporal CT images for pulmonary nodules detection
Author(s): Jichao Yan; Luan Jiang; Qiang Li
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Paper Abstract

Interpretation of temporal CT images could help the radiologists to detect some subtle interval changes in the sequential examinations. The purpose of this study was to develop a fully automated scheme for accurate registration of temporal CT images for pulmonary nodule detection. Our method consisted of three major registration steps. Firstly, affine transformation was applied in the segmented lung region to obtain global coarse registration images. Secondly, B-splines based free-form deformation (FFD) was used to refine the coarse registration images. Thirdly, Demons algorithm was performed to align the feature points extracted from the registered images in the second step and the reference images. Our database consisted of 91 temporal CT cases obtained from Beijing 301 Hospital and Shanghai Changzheng Hospital. The preliminary results showed that approximately 96.7% cases could obtain accurate registration based on subjective observation. The subtraction images of the reference images and the rigid and non-rigid registered images could effectively remove the normal structures (i.e. blood vessels) and retain the abnormalities (i.e. pulmonary nodules). This would be useful for the screening of lung cancer in our future study.

Paper Details

Date Published: 24 February 2017
PDF: 6 pages
Proc. SPIE 10133, Medical Imaging 2017: Image Processing, 101332J (24 February 2017); doi: 10.1117/12.2254660
Show Author Affiliations
Jichao Yan, Shanghai United Imaging Healthcare Co., Ltd. (China)
Luan Jiang, Shanghai United Imaging Healthcare Co., Ltd. (China)
Shanghai Advanced Research Institute (China)
Qiang Li, Shanghai United Imaging Healthcare Co., Ltd. (China)
Shanghai Advanced Research Institute (China)


Published in SPIE Proceedings Vol. 10133:
Medical Imaging 2017: Image Processing
Martin A. Styner; Elsa D. Angelini, Editor(s)

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