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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xiuying Wang Chaojie Zheng Jinhu Chen Yong Yin Dagan Feng |
| Copyright Year | 2012 |
| Description | Author affiliation: BMIT research group, Australia (Dagan Feng) || Biomedical and Multimedia Information Technology (BMIT) research group, School of Information Technologies, The University of Sydney, Australia (Chaojie Zheng) || Department of Radiation Oncology, Shandong Tumor Hospital, Jinan, China (Jinhu Chen; Yong Yin) || BMIT research group, The University of Sydney, Australia (Xiuying Wang) |
| Abstract | Deformable registration is essential to map the radiotherapy plan onto treatment images of the patient. However, deformable registration may introduce excessive deformation into tumor volume, shape and location. In this paper, our proposed registration method aims to correct the local excessive deformation on tumor while retaining the global correspondence by conventional registration method. To trace the excessive tumor change, automatic landmark correspondence is established on the basis of genus zero surface conformal mapping to recover the tumor information and its surrounding structures. Our experimental validation on clinical PET volumes and CT volumes demonstrated that our registration method was able to construct global correspondence for the input volumes and in the meantime maintain the correct and meaningful tumor information. |
| Starting Page | 824 |
| Ending Page | 827 |
| File Size | 989080 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781457721762 |
| e-ISBN | 9781457721779 |
| e-ISBN | 9781457721755 |
| DOI | 10.1109/BHI.2012.6211712 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-01-05 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Shape Computed tomography Lungs Lesions Positron emission tomography Accuracy |
| Content Type | Text |
| Resource Type | Article |
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