A Semi-Automatic Algorithm for Estimating Cobb Angle

Safari, Ali; Parsaei, Hossein; Zamani, Ali; Tahvildari, Babak Pourabbas

doi:10.31661/jbpe.v9i3jun.730

Cited by 25 publications

(21 citation statements)

References 16 publications

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“…Among the others, Cobb method is widely used and well accepted standard for scoliosis diagnosis and treatment decisions. However, the manual measurement of Cobb angle shows poor accuracy due to the large anatomical variation of patients from different age group and the low tissue contrast of X-ray spinal image 2 . This gives raise to undesired inter-observer and intra-observer variability.…”

Section: Introductionmentioning

confidence: 99%

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

Thalengala

Bhat

Anitha

2021

Sci Rep

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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.

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Section: Introductionmentioning

confidence: 99%

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

Thalengala

Bhat

Anitha

2021

Sci Rep

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“…In a recent study, Zhang et al proposed an automatic method for Cobb angle measurement and compare the results with 2D manual measurement in which the mean differences were 2.9° in mild group (Cobb angle <25°), 3.7° in moderate group (Cobb angle between 25° and 45°) and 3.9° in severe group (Cobb angle <45°), respectively (17). In addition, Safari et al newly developed a semi-automatic algorithm to estimate Cobb angle, which was user-friendly and reliable with a correlation coefficient of 0.81 (18).…”

Section: Discussionmentioning

confidence: 99%

Comparison of 3D and 2D characterization of spinal geometry from biplanar X-rays: a large cohort study

Hu¹,

Vergari²,

Gajny³

et al. 2021

Quant Imaging Med Surg

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Background: Biplanar X-ray system providing anteroposterior and sagittal plane with an ultra-low radiation dose and in weight-bearing position is increasingly used for spine imaging. The original threedimensional (3D) reconstruction method from biplanar X-rays has been widely used for clinical parameters, however, the main issue is that manual adjustments of the 3D model was quite time-consuming and limited to thoracolumbar spine. A quasi-automated 3D reconstruction method of the spine from cervical vertebra to pelvis was proposed, which proved fast and accurate in 57 patients with adolescent idiopathic scoliosis. The aim of this study was to compare the newly developed technique of quasi-automatic 3D measurement with classical 2D measurements in a large cohort.Methods: A total of 494 adults with biplanar EOS X-ray scanning were included in this study and divided into health and deformity group according to the presence of spinal deformity. The proposed method of quasi-automatic 3D measurement was applied to all these subjects. The radiographic parameters included: thoracic kyphosis (TK), lumbar lordosis (LL), pelvic incidence (PI), pelvic tilt (PT), sagittal vertical axis (SVA), T1 pelvic angle (TPA) in sagittal plane, and cobb angle in coronal plane. Comparison was made between quasi-automatic and manual measurement. Results:The mean age was 53.7±19.9 years old. In the whole population, the mean differences between the two methods were 3.9° for TK (30.5°±9.9° vs.

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“…В качестве одной из ключевых задач была выбрана подготовка данных, и значительное внимание уделено созданию датасета рентгенограмм для обучения нейросети. Если большинство результатов исследований базировалось на анализе 14-49 рентгенограмм, то мы провели обучение сети на 300 цифровых рентгенограммах позвоночника больных идиопатическим сколиозом, предварительно расчерченных врачомрентгенологом [9][10][11][12][13][14]25]. Сопоставимый объем исследований прослежен только в работах J. Wang et al и Y. Pan et al [11,13].…”

Section: Discussionunclassified

“…Анализ литературы показал, что за последние 10 лет выполнено большое количество работ, посвященных цифровым программным решениям при вычислении величины угла Кобба на рентгенограммах, причем увеличение количества таких исследований в первую очередь обусловлено развитием цифровой рентгенографии [9][10][11][12][13]. В то же время предлагаемые решения фактически являются либо полуавтоматическими в ситуациях, когда врач определяет начальный и конечный позвонки дуг, либо полностью ручными, но с использованием программного обеспечения, позволяющего увеличить изображение и более точно провести касательные к проекции тела позвонка [14]. Существует возможность применения смартфонов для измерений степени деформации, а также программы Microsoft PowerPoint [15,16], но данные измерения производятся не в автоматическом режиме и обладают теми же недостатками, что и десктопные приложения.…”

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Automation analysis X-ray of the spine to objectify the assessment of the severity of scoliotic deformity in idiopathic scoliosis: a preliminary report

Lein¹,

Nechaeva²,

Mammadova³

et al. 2020

Pediatr Traum Orthop Reconstr Surg

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Background. A large number of studies have focused on automating the process of measuring the Cobb angle. Although there is no practical tool to assist doctors with estimating the severity of the curvature of the spine and determine the best suitable treatment type. Aim. We aimed to examine the algorithms used for distinguishing vertebral column, vertebrae, and for building a tangent on the X-ray photographs. The superior algorithms should be implemented into the clinical practice as an instrument of automatic analysis of the spine X-rays in scoliosis patients. Materials and methods. A total of 300 digital X-rays of the spine of children with idiopathic scoliosis were gathered. The X-rays were manually ruled by a radiologist to determine the Cobb angle. This data was included into the main dataset used for training and validating the neural network. In addition, the Sliding Window Method algorithm was implemented and compared with the machine learning algorithms, proving it to be vastly superior in the context of this research. Results. This research can serve as the foundation for the future development of an automated system for analyzing spine X-rays. This system allows processing of a large amount of data for achieving 85% in training neural network to determine the Cobb angle. Conclusions. This research is the first step toward the development of a modern innovative product that uses artificial intelligence for distinguishing the different portions of the spine on 2D X-ray images for building the lines required to determine the Cobb angle.

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A Semi-Automatic Algorithm for Estimating Cobb Angle

Cited by 25 publications

References 16 publications

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

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

Comparison of 3D and 2D characterization of spinal geometry from biplanar X-rays: a large cohort study

Automation analysis X-ray of the spine to objectify the assessment of the severity of scoliotic deformity in idiopathic scoliosis: a preliminary report

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