Automated non-contact measurement of the spine curvature at the sagittal plane using a deep neural network-Reference-Cited by-同舟云学术

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Automated non-contact measurement of the spine curvature at the sagittal plane using a deep neural network

Published:2024-01 Issue: Volume:111 Page:106146
ISSN:0268-0033
Container-title:Clinical Biomechanics
language:en
Short-container-title:Clinical Biomechanics

Author:

Park Sangsoo,Yoo Hyun-Joon,Jang Jin Su,Lee Sang-Heon

Funder

National Research Foundation of Korea

Ministry of Education

Publisher

Elsevier BV

Subject

Orthopedics and Sports Medicine,Biophysics

Reference46 articles.

1. 2d human pose estimation: new benchmark and state of the art analysis;Andriluka;Proc. IEEE Conf. Comput. Vis. Pattern Recognit.,2014

2. Reliability and validity of non-radiographic methods of thoracic kyphosis measurement: a systematic review;Barrett;Man. Ther.,2014

3. Analysis of the sagittal balance of the spine and pelvis using shape and orientation parameters;Berthonnaud;Clinical Spine Surgery,2005

4. Realtime multi-person 2d pose estimation using part affinity fields;Cao,2017

5. OpenPose: realtime multi-person 2D pose estimation using part affinity fields;Cao;IEEE Trans. Pattern Anal. Mach. Intell.,2019

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