Automated Localization of Pelvic Anatomical Coordinate System from 3D CT Data of the Hip Using Statistical Atlas
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- YOKOTA Futoshi
- Department of Computer Science and Systems Engineering, Graduate School of Engineering, Kobe University
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- OKADA Toshiyuki
- Department of Radiology, Graduate School of Medicine, Osaka University
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- TAKAO Masaki
- Department of Orthopaedic Surgery, Graduate School of Medicine, Osaka University
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- SUGANO Nobuhiko
- Department of Orthopaedic Medical Engineering, Graduate School of Medicine, Osaka University
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- TADA Yukio
- Department of System Science, Graduate School of System informatics, Kobe University
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- TOMIYAMA Noriyuki
- Department of Radiology, Graduate School of Medicine, Osaka University
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- SATO Yoshinobu
- Department of Radiology, Graduate School of Medicine, Osaka University
Bibliographic Information
- Other Title
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- 統計アトラスを用いた股関節三次元CT画像からの骨盤解剖学的座標系の自動設定
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Abstract
Localization of the pelvic anatomical coordinate system is a prerequisite for patient-specific preoperative planning and joint motion simulation for hip surgery. Our aim is to automate localization of the pelvic anatomical coordinate system from 3D CT data. In this paper, we propose a statistical atlas-based method that consists of three steps. The first step is spatial normalization using a probabilistic atlas. The second step is feature point recognition using a statistical landmark model. The final step is coordinate system refinement using a standard CT atlas. We applied the proposed method to 39 datasets. Compared to manual localization by an experienced surgeon, the average positional error was 2.37 ± 1.30 mm and the average orientation error was 1.07 ± 0.50 degrees. These results demonstrate the usefulness of the proposed method.
Journal
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- Medical Imaging Technology
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Medical Imaging Technology 30 (1), 43-52, 2012
The Japanese Society of Medical Imaging Technology
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Keywords
Details 詳細情報について
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- CRID
- 1390001204654224256
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- NII Article ID
- 130002049725
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- ISSN
- 21853193
- 0288450X
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- Data Source
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- JaLC
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed