A Registration Method Based on Contour Point Cloud for 3D Whole-Body PET and CT Images
Joint Authors
Song, Zhiying
Yang, Qiyao
Wang, Zhiguo
Zhang, Guoxu
Jiang, Huiyan
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-02-21
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
The PET and CT fusion image, combining the anatomical and functional information, has important clinical meaning.
An effective registration of PET and CT images is the basis of image fusion.
This paper presents a multithread registration method based on contour point cloud for 3D whole-body PET and CT images.
Firstly, a geometric feature-based segmentation (GFS) method and a dynamic threshold denoising (DTD) method are creatively proposed to preprocess CT and PET images, respectively.
Next, a new automated trunk slices extraction method is presented for extracting feature point clouds.
Finally, the multithread Iterative Closet Point is adopted to drive an affine transform.
We compare our method with a multiresolution registration method based on Mattes Mutual Information on 13 pairs (246~286 slices per pair) of 3D whole-body PET and CT data.
Experimental results demonstrate the registration effectiveness of our method with lower negative normalization correlation (NC = −0.933) on feature images and less Euclidean distance error (ED = 2.826) on landmark points, outperforming the source data (NC = −0.496, ED = 25.847) and the compared method (NC = −0.614, ED = 16.085).
Moreover, our method is about ten times faster than the compared one.
American Psychological Association (APA)
Song, Zhiying& Jiang, Huiyan& Yang, Qiyao& Wang, Zhiguo& Zhang, Guoxu. 2017. A Registration Method Based on Contour Point Cloud for 3D Whole-Body PET and CT Images. BioMed Research International،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1137606
Modern Language Association (MLA)
Song, Zhiying…[et al.]. A Registration Method Based on Contour Point Cloud for 3D Whole-Body PET and CT Images. BioMed Research International No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1137606
American Medical Association (AMA)
Song, Zhiying& Jiang, Huiyan& Yang, Qiyao& Wang, Zhiguo& Zhang, Guoxu. A Registration Method Based on Contour Point Cloud for 3D Whole-Body PET and CT Images. BioMed Research International. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1137606
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1137606