AIMC Topic: Scoliosis
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An algorithm for using deep learning convolutional neural networks with three dimensional depth sensor imaging in scoliosis detection.
The spine journal : official journal of the North American Spine Society
Feb 1, 2021
BACKGROUND CONTEXT: Timely intervention in growing individuals, such as brace treatment, relies on early detection of adolescent idiopathic scoliosis (AIS). To this end, several screening methods have been implemented. However, these methods have lim...
Artificial Intelligence Models Predict Operative Versus Nonoperative Management of Patients with Adult Spinal Deformity with 86% Accuracy.
World neurosurgery
May 17, 2020
OBJECTIVE: Patients with ASD show complex and highly variable disease. The decision to manage patients operatively is largely subjective and varies based on surgeon training and experience. We sought to develop models capable of accurately discrimina...
A convolutional neural network to detect scoliosis treatment in radiographs.
International journal of computer assisted radiology and surgery
Apr 26, 2020
PURPOSE: The aim of this work is to propose a classification algorithm to automatically detect treatment for scoliosis (brace, implant or no treatment) in postero-anterior radiographs. Such automatic labelling of radiographs could represent a step to...
Development and validation of deep learning algorithms for scoliosis screening using back images.
Communications biology
Oct 25, 2019
Adolescent idiopathic scoliosis is the most common spinal disorder in adolescents with a prevalence of 0.5-5.2% worldwide. The traditional methods for scoliosis screening are easily accessible but require unnecessary referrals and radiography exposur...
Evaluation of a computer-aided method for measuring the Cobb angle on chest X-rays.
European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
Aug 24, 2019
OBJECTIVES: To automatically measure the Cobb angle and diagnose scoliosis on chest X-rays, a computer-aided method was proposed and the reliability and accuracy were evaluated.
Accurate automated Cobb angles estimation using multi-view extrapolation net.
Medical image analysis
Aug 9, 2019
Accurate automated quantitative Cobb angle estimation that quantitatively evaluates scoliosis plays an important role in scoliosis diagnosis and treatment. It solves the problem of the traditional manual method, which is the current clinical standard...
Vertebrae Identification and Localization Utilizing Fully Convolutional Networks and a Hidden Markov Model.
IEEE transactions on medical imaging
Jul 8, 2019
Automated identification and localization of vertebrae in spinal computed tomography (CT) imaging is a complicated hybrid task. This task requires detecting and indexing a long sequence in a 3-D image, and both image feature extraction and sequence m...
Toward Automated 3D Spine Reconstruction from Biplanar Radiographs Using CNN for Statistical Spine Model Fitting.
IEEE transactions on medical imaging
May 3, 2019
To date, 3D spine reconstruction from biplanar radiographs involves intensive user supervision and semi-automated methods that are time-consuming and not effective in clinical routine. This paper proposes a new, fast, and automated 3D spine reconstru...
Cobb Angle Measurement of Spine from X-Ray Images Using Convolutional Neural Network.
Computational and mathematical methods in medicine
Feb 19, 2019
Scoliosis is a common spinal condition where the spine curves to the side and thus deforms the spine. Curvature estimation provides a powerful index to evaluate the deformation severity of scoliosis. In current clinical diagnosis, the standard curvat...
Prediction of spinal curve progression in Adolescent Idiopathic Scoliosis using Random Forest regression.
Computers in biology and medicine
Oct 4, 2018
BACKGROUND: The progression of the spinal curve represents one of the major concerns in the assessment of Adolescent Idiopathic Scoliosis (AIS). The prediction of the shape of the spine from the first visit could guide the management of AIS and provi...
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