Paediatric syndromic scoliosis: proceedings of the half-day course at the 57th annual meeting of the Scoliosis Research Society

Mehta, Jwalant S.; Pahys, Joshua M.; Saad, Ahmed; Sponseller, Paul; Andras, Lindsay; Marks, David; Poon, Selina; Klineberg, Eric; White, Klane K.; Helenius, Ilkka; Welborn, Michelle; Redding, Greg

doi:10.1007/s43390-024-00822-1

Spine Deform

2024

DOI: 10.1007/s43390-024-00822-1

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Paediatric syndromic scoliosis: proceedings of the half-day course at the 57th annual meeting of the Scoliosis Research Society

Jwalant S. Mehta,

Joshua M. Pahys,

Ahmed Saad

et al.

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Intelligent Evaluation Method for Scoliosis at Home Using Back Photos Captured by Mobile Phones

Li,

Peng,

Mao

et al. 2024

Bioengineering

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The traditional scoliosis examination based on X-ray film is not suitable for large-scale screening, and it is also not suitable for dynamic evaluation during rehabilitation. Therefore, based on computer vision technology, this paper puts forward an evaluation method of scoliosis with different photos of the back taken by mobile phones, which involves three aspects: first, based on the key point detection model of YOLOv8, an algorithm for judging the type of spinal coronal curvature is proposed; second, an algorithm for evaluating the coronal plane of the spine based on the key points of the human back is proposed, aiming at quantifying the deviation degree of the spine in the coronal plane; third, the measurement algorithm of trunk rotation (ATR angle) based on multi-scale automatic peak detection (AMPD) is proposed, aiming at quantifying the deviation degree of the spine in sagittal plane. The public dataset and clinical paired data (mobile phone photo and X-ray) are used to test. The results show that this method has high accuracy and effectiveness in distinguishing the type of spinal curvature and evaluating the degree of deviation, which is higher than other deep learning algorithms.

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Intelligent Evaluation Method for Scoliosis at Home Using Back Photos Captured by Mobile Phones

Li,

Peng,

Mao

et al. 2024

Bioengineering

View full text Add to dashboard Cite

show abstract

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Paediatric syndromic scoliosis: proceedings of the half-day course at the 57th annual meeting of the Scoliosis Research Society

Cited by 1 publication

References 124 publications

Intelligent Evaluation Method for Scoliosis at Home Using Back Photos Captured by Mobile Phones

Intelligent Evaluation Method for Scoliosis at Home Using Back Photos Captured by Mobile Phones

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