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Title: X-ray2Shape: Reconstruction of 3D Liver Shape from a Single 2D Projection Image
Authors: Tong, Fei
Nakao, Megumi  kyouindb  KAKEN_id  orcid https://orcid.org/0000-0002-5508-4366 (unconfirmed)
Wu, Shuqiong
Nakamura, Mitsuhiro
Matsuda, Tetsuya  kyouindb  KAKEN_id  orcid https://orcid.org/0000-0002-2339-1521 (unconfirmed)
Author's alias: 中尾, 恵
中村, 光宏
松田, 哲也
Keywords: Shape
Three-dimensional displays
Liver
Feature extraction
X-ray imaging
Two dimensional displays
Image reconstruction
Issue Date: 2020
Publisher: Institute of Electrical and Electronics Engineers Inc.
Journal title: 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Start page: 1608
End page: 1611
Thesis number: 9176655
Abstract: Computed tomography (CT) and magnetic resonance imaging (MRI) scanners measure three-dimensional (3D) images of patients. However, only low-dimensional local two-dimensional (2D) images may be obtained during surgery or radiotherapy. Although computer vision techniques have shown that 3D shapes can be estimated from multiple 2D images, shape reconstruction from a single 2D image such as an endoscopic image or an X-ray image remains a challenge. In this study, we propose X-ray2Shape, which permits a deep learning-based 3D organ mesh to be reconstructed from a single 2D projection image. The method learns the mesh deformation from a mean template and deep features computed from the individual projection images. Experiments with organ meshes and digitally reconstructed radiograph (DRR) images of abdominal regions were performed to confirm the estimation performance of the methods.
Description: [2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 20-24 July 2020, Montreal, QC, Canada]
Rights: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
This is not the published version. Please cite only the published version. この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。
URI: http://hdl.handle.net/2433/265386
DOI(Published Version): 10.1109/EMBC44109.2020.9176655
PubMed ID: 33018302
Appears in Collections:Journal Articles

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