2D–3D reconstruction of distal forearm bone from actual X-ray images of the wrist using convolutional neural networks

Abstract The purpose of the study was to develop a deep learning network for estimating and constructing highly accurate 3D bone models directly from actual X-ray images and to verify its accuracy. The data used were 173 computed tomography (CT) images and 105 actual X-ray images of a healthy wrist...

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Autores principales:	Ryoya Shiode, Mototaka Kabashima, Yuta Hiasa, Kunihiro Oka, Tsuyoshi Murase, Yoshinobu Sato, Yoshito Otake
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/83675418f1a14881943041ec4d68ec1a
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spelling	oai:doaj.org-article:83675418f1a14881943041ec4d68ec1a2021-12-02T16:31:02Z2D–3D reconstruction of distal forearm bone from actual X-ray images of the wrist using convolutional neural networks10.1038/s41598-021-94634-22045-2322https://doaj.org/article/83675418f1a14881943041ec4d68ec1a2021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-94634-2https://doaj.org/toc/2045-2322Abstract The purpose of the study was to develop a deep learning network for estimating and constructing highly accurate 3D bone models directly from actual X-ray images and to verify its accuracy. The data used were 173 computed tomography (CT) images and 105 actual X-ray images of a healthy wrist joint. To compensate for the small size of the dataset, digitally reconstructed radiography (DRR) images generated from CT were used as training data instead of actual X-ray images. The DRR-like images were generated from actual X-ray images in the test and adapted to the network, and high-accuracy estimation of a 3D bone model from a small data set was possible. The 3D shape of the radius and ulna were estimated from actual X-ray images with accuracies of 1.05 ± 0.36 and 1.45 ± 0.41 mm, respectively.Ryoya ShiodeMototaka KabashimaYuta HiasaKunihiro OkaTsuyoshi MuraseYoshinobu SatoYoshito OtakeNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Ryoya Shiode Mototaka Kabashima Yuta Hiasa Kunihiro Oka Tsuyoshi Murase Yoshinobu Sato Yoshito Otake 2D–3D reconstruction of distal forearm bone from actual X-ray images of the wrist using convolutional neural networks
description	Abstract The purpose of the study was to develop a deep learning network for estimating and constructing highly accurate 3D bone models directly from actual X-ray images and to verify its accuracy. The data used were 173 computed tomography (CT) images and 105 actual X-ray images of a healthy wrist joint. To compensate for the small size of the dataset, digitally reconstructed radiography (DRR) images generated from CT were used as training data instead of actual X-ray images. The DRR-like images were generated from actual X-ray images in the test and adapted to the network, and high-accuracy estimation of a 3D bone model from a small data set was possible. The 3D shape of the radius and ulna were estimated from actual X-ray images with accuracies of 1.05 ± 0.36 and 1.45 ± 0.41 mm, respectively.
format	article
author	Ryoya Shiode Mototaka Kabashima Yuta Hiasa Kunihiro Oka Tsuyoshi Murase Yoshinobu Sato Yoshito Otake
author_facet	Ryoya Shiode Mototaka Kabashima Yuta Hiasa Kunihiro Oka Tsuyoshi Murase Yoshinobu Sato Yoshito Otake
author_sort	Ryoya Shiode
title	2D–3D reconstruction of distal forearm bone from actual X-ray images of the wrist using convolutional neural networks
title_short	2D–3D reconstruction of distal forearm bone from actual X-ray images of the wrist using convolutional neural networks
title_full	2D–3D reconstruction of distal forearm bone from actual X-ray images of the wrist using convolutional neural networks
title_fullStr	2D–3D reconstruction of distal forearm bone from actual X-ray images of the wrist using convolutional neural networks
title_full_unstemmed	2D–3D reconstruction of distal forearm bone from actual X-ray images of the wrist using convolutional neural networks
title_sort	2d–3d reconstruction of distal forearm bone from actual x-ray images of the wrist using convolutional neural networks
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/83675418f1a14881943041ec4d68ec1a
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_version_	1718383885113360384

2D–3D reconstruction of distal forearm bone from actual X-ray images of the wrist using convolutional neural networks

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