Computerized image understanding system for reliable estimation of spinal curvature in idiopathic scoliosis

Abstract Analysis of scoliosis requires thorough radiographic evaluation by spinal curvature estimation to completely assess the spinal deformity. Spinal curvature estimation gives orthopaedic surgeons an idea of severity of spinal deformity for therapeutic purposes. Manual intervention has always b...

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Autores principales:	Ananthakrishna Thalengala, Shyamasunder N. Bhat, H. Anitha
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/ceb49bc63a0741c9b6b900eb665b75ff
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spelling	oai:doaj.org-article:ceb49bc63a0741c9b6b900eb665b75ff2021-12-02T18:18:06ZComputerized image understanding system for reliable estimation of spinal curvature in idiopathic scoliosis10.1038/s41598-021-86436-32045-2322https://doaj.org/article/ceb49bc63a0741c9b6b900eb665b75ff2021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-86436-3https://doaj.org/toc/2045-2322Abstract Analysis of scoliosis requires thorough radiographic evaluation by spinal curvature estimation to completely assess the spinal deformity. Spinal curvature estimation gives orthopaedic surgeons an idea of severity of spinal deformity for therapeutic purposes. Manual intervention has always been an issue to ensure accuracy and repeatability. Computer assisted systems are semi-automatic and is still influenced by surgeon’s expertise. Spinal curvature estimation completely relies on accurate identification of required end vertebrae like superior end-vertebra, inferior end-vertebra and apical vertebra. In the present work, automatic extraction of spinal information central sacral line and medial axis by computerized image understanding system has been proposed. The inter-observer variability in the anatomical landmark identification is quantified using Kappa statistic. The resultant Kappa value computed between proposed algorithm and observer lies in the range 0.7 and 0.9, which shows good accuracy. Identification of the required end vertebra is automated by the extracted spinal information. Difference in inter and intra-observer variability for the state of the art computer assisted and proposed system are quantified in terms of mean absolute difference for the various types (Type-I, Type-II, Type-III, Type-IV, and Type-V) of scoliosis.Ananthakrishna ThalengalaShyamasunder N. BhatH. AnithaNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Ananthakrishna Thalengala Shyamasunder N. Bhat H. Anitha Computerized image understanding system for reliable estimation of spinal curvature in idiopathic scoliosis
description	Abstract Analysis of scoliosis requires thorough radiographic evaluation by spinal curvature estimation to completely assess the spinal deformity. Spinal curvature estimation gives orthopaedic surgeons an idea of severity of spinal deformity for therapeutic purposes. Manual intervention has always been an issue to ensure accuracy and repeatability. Computer assisted systems are semi-automatic and is still influenced by surgeon’s expertise. Spinal curvature estimation completely relies on accurate identification of required end vertebrae like superior end-vertebra, inferior end-vertebra and apical vertebra. In the present work, automatic extraction of spinal information central sacral line and medial axis by computerized image understanding system has been proposed. The inter-observer variability in the anatomical landmark identification is quantified using Kappa statistic. The resultant Kappa value computed between proposed algorithm and observer lies in the range 0.7 and 0.9, which shows good accuracy. Identification of the required end vertebra is automated by the extracted spinal information. Difference in inter and intra-observer variability for the state of the art computer assisted and proposed system are quantified in terms of mean absolute difference for the various types (Type-I, Type-II, Type-III, Type-IV, and Type-V) of scoliosis.
format	article
author	Ananthakrishna Thalengala Shyamasunder N. Bhat H. Anitha
author_facet	Ananthakrishna Thalengala Shyamasunder N. Bhat H. Anitha
author_sort	Ananthakrishna Thalengala
title	Computerized image understanding system for reliable estimation of spinal curvature in idiopathic scoliosis
title_short	Computerized image understanding system for reliable estimation of spinal curvature in idiopathic scoliosis
title_full	Computerized image understanding system for reliable estimation of spinal curvature in idiopathic scoliosis
title_fullStr	Computerized image understanding system for reliable estimation of spinal curvature in idiopathic scoliosis
title_full_unstemmed	Computerized image understanding system for reliable estimation of spinal curvature in idiopathic scoliosis
title_sort	computerized image understanding system for reliable estimation of spinal curvature in idiopathic scoliosis
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/ceb49bc63a0741c9b6b900eb665b75ff
work_keys_str_mv	AT ananthakrishnathalengala computerizedimageunderstandingsystemforreliableestimationofspinalcurvatureinidiopathicscoliosis AT shyamasundernbhat computerizedimageunderstandingsystemforreliableestimationofspinalcurvatureinidiopathicscoliosis AT hanitha computerizedimageunderstandingsystemforreliableestimationofspinalcurvatureinidiopathicscoliosis
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Computerized image understanding system for reliable estimation of spinal curvature in idiopathic scoliosis

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