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Pulmonary Motion Tracking from 4D-CT Images Using a 3D-KLT Tracker
https://repo.qst.go.jp/records/69938
https://repo.qst.go.jp/records/699381f307e98-daed-4c16-abd0-e220bf472faa
Item type | 会議発表用資料 / Presentation(1) | |||||
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公開日 | 2009-11-12 | |||||
タイトル | ||||||
タイトル | Pulmonary Motion Tracking from 4D-CT Images Using a 3D-KLT Tracker | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_c94f | |||||
資源タイプ | conference object | |||||
アクセス権 | ||||||
アクセス権 | metadata only access | |||||
アクセス権URI | http://purl.org/coar/access_right/c_14cb | |||||
著者 |
Kubota, Yoshiki
× Kubota, Yoshiki× Aoki, Kota× Nagahashi, Hiroshi× Minohara, Shinichi× 蓑原 伸一 |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | We propose a new method for lung-motion tracking and its quantification from 4-dimensional X-ray computed tomographic (4DCT) images. This method uses an enhanced 3D-KLT tracker. An advantage of our method is that it can find many feature points (regions) for tracking that are not restricted to the bifurcation points of bronchi or vessels. The feature point extraction algorithm depends only on image gradients. Moreover, our method adopts a hierarchical tracking based on pyramidal image structure. This provides robustness for large movements of the objects. Lung motion is quantified by tracking a large number of feature points in the lung. In this paper, we first evaluate the performance of our proposed method for artificial 4D-CT images and then describe quantification results of real 4D-CT images. Our experimental results clearly show that lung movement is not a simple translation but an oval pattern. | |||||
会議概要(会議名, 開催地, 会期, 主催者等) | ||||||
内容記述タイプ | Other | |||||
内容記述 | Nuclear Science Symposium and Medical Imaging Conference | |||||
発表年月日 | ||||||
日付 | 2009-10-31 | |||||
日付タイプ | Issued |