Fragility fracture detection with 3D CT images in the pelvis like the boring survey
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- Yamamoto Naoto
- University of Hyogo, Himeji, Japan
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- Rashedur Rahman
- University of Hyogo, Himeji, Japan
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- Yagi Naomi
- Himeji Dokkyo University, Himeji, Japan
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- Hayashi Keigo
- Steel Memorial Hirihata Hospital, Himeji, Japan
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- Maruo Akihiro
- Steel Memorial Hirihata Hospital, Himeji, Japan
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- Muratsu Hirotsugu
- Steel Memorial Hirihata Hospital, Himeji, Japan
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- Kobashi Shoji
- University of Hyogo, Himeji, Japan
Bibliographic Information
- Other Title
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- 3次元CT画像を用いた模擬ボーリング調査による脆弱性骨盤骨折検出法
Abstract
<p>In Japan of a super-aging society, the number of patients suffering from fragility fracture of the pelvis (FFP) with osteoporosis is increasing. It can make patients bedridden and the complication. Physicians diagnose the fracture in 3D CT images, which is hard and time-consuming to find FFP. This paper proposes a novel method of boring survey based fracture detection (BSFD), to automatically detect FFP in 3D CT images. Firstly, the bone surface of the pelvis is extracted from CT images. Then, it bores the quadratic prism for the internal bone area with CT values. The 3D convolutional neural network can predict a probability of fracture, and apply to the whole pelvis. The method was evaluated by using 110 elderly subjects with pelvic fractures. The AUC was 0.84 for training subjects and 0.77 for evaluation subjects.In addition, it is useful for physicians to display the 3D distribution of fracture possibilities.</p>
Journal
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- Transactions of Japanese Society for Medical and Biological Engineering
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Transactions of Japanese Society for Medical and Biological Engineering Annual59 (Abstract), 296-296, 2021
Japanese Society for Medical and Biological Engineering
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Details 詳細情報について
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- CRID
- 1390571240018105600
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- NII Article ID
- 130008105198
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- ISSN
- 18814379
- 1347443X
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- Text Lang
- ja
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- Data Source
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- JaLC
- CiNii Articles
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- Abstract License Flag
- Disallowed