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Intelligent analysis of coronal alignment in lower limbs based on radiographic image with convolutional neural network
DC Field | Value | Language |
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dc.contributor.author | 이우석 | - |
dc.date.accessioned | 2021-05-21T17:11:53Z | - |
dc.date.available | 2021-05-21T17:11:53Z | - |
dc.date.issued | 2020-05 | - |
dc.identifier.issn | 0010-4825 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/182761 | - |
dc.description.abstract | One of the first tasks in osteotomy and arthroplasty is to identify the lower limb varus and valgus deformity status. The measurement of a set of angles to determine this status is generally performed manually with the measurement accuracy depending heavily on the experience of the person performing the measurements. This study proposes a method for calculating the required angles in lower limb radiographic (X-ray) images supported by the convolutional neural network. To achieved high accuracy in the measuring process, not only is a decentralized deep learning algorithm, including two orders for the radiographic, utilized, but also a training dataset is built based on the geometric knowledge related to the deformity correction principles. The developed algorithm performance is compared with standard references consisting of manually measured values provided by doctors in 80 radiographic images exhibiting an impressively low deviation of less than 1.5° in 82.3% of the cases. | - |
dc.description.statementOfResponsibility | restriction | - |
dc.language | English | - |
dc.publisher | Elsevier | - |
dc.relation.isPartOf | COMPUTERS IN BIOLOGY AND MEDICINE | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.title | Intelligent analysis of coronal alignment in lower limbs based on radiographic image with convolutional neural network | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Orthopedic Surgery (정형외과학교실) | - |
dc.contributor.googleauthor | Thong Phi Nguyen | - |
dc.contributor.googleauthor | Dong-Sik Chae | - |
dc.contributor.googleauthor | Sung-Jun Park | - |
dc.contributor.googleauthor | Kyung-Yil Kang | - |
dc.contributor.googleauthor | Woo-Suk Lee | - |
dc.contributor.googleauthor | Jonghun Yoon | - |
dc.identifier.doi | 10.1016/j.compbiomed.2020.103732 | - |
dc.contributor.localId | A02992 | - |
dc.relation.journalcode | J00638 | - |
dc.identifier.eissn | 1879-0534 | - |
dc.identifier.pmid | 32250859 | - |
dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S0010482520301153 | - |
dc.subject.keyword | Convolution neural network | - |
dc.subject.keyword | Lower limbs osteotomy | - |
dc.subject.keyword | X-rays | - |
dc.contributor.alternativeName | Lee, Woo Suk | - |
dc.contributor.affiliatedAuthor | 이우석 | - |
dc.citation.volume | 120 | - |
dc.citation.startPage | 103732 | - |
dc.identifier.bibliographicCitation | COMPUTERS IN BIOLOGY AND MEDICINE, Vol.120 : 103732, 2020-05 | - |
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