Machine Learning Applications of Surgical Imaging for the Diagnosis and Treatment of Spine Disorders: Current State of the Art
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Title
Machine Learning Applications of Surgical Imaging for the Diagnosis and Treatment of Spine Disorders: Current State of the Art
Authors
Keywords
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Journal
NEUROSURGERY
Volume Publish Ahead of Print, Issue -, Pages -
Publisher
Ovid Technologies (Wolters Kluwer Health)
Online
2022-02-02
DOI
10.1227/neu.0000000000001853
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Note: Only part of the references are listed.- Magnetic resonance imaging–based synthetic computed tomography of the lumbar spine for surgical planning: a clinical proof-of-concept
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- (2020) Timothy A. Damron et al. JOURNAL OF ORTHOPAEDIC RESEARCH
- DoseGAN: a generative adversarial network for synthetic dose prediction using attention-gated discrimination and generation
- (2020) Vasant Kearney et al. Scientific Reports
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- (2019) David S Watson et al. BMJ-British Medical Journal
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- (2019) Benjamin Hopkins et al. World Neurosurgery
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- (2019) Fabio Galbusera et al. EUROPEAN SPINE JOURNAL
- Cobb Angle Measurement of Spine from X-Ray Images Using Convolutional Neural Network
- (2019) Ming-Huwi Horng et al. Computational and Mathematical Methods in Medicine
- Machine learning for automated 3-dimensional segmentation of the spine and suggested placement of pedicle screws based on intraoperative cone-beam computer tomography
- (2019) Gustav Burström et al. JOURNAL OF NEUROSURGERY-SPINE
- Augmented reality and artificial intelligence-based navigation during percutaneous vertebroplasty: a pilot randomised clinical trial
- (2019) Pierre Auloge et al. EUROPEAN SPINE JOURNAL
- Artificial Intelligence for the Treatment of Lumbar Spondylolisthesis
- (2019) Zoher Ghogawala et al. NEUROSURGERY CLINICS OF NORTH AMERICA
- Evaluation of a computer-aided method for measuring the Cobb angle on chest X-rays
- (2019) Yaling Pan et al. EUROPEAN SPINE JOURNAL
- Machine learning applications to clinical decision support in neurosurgery: an artificial intelligence augmented systematic review
- (2019) Quinlan D. Buchlak et al. NEUROSURGICAL REVIEW
- Strengths, Weaknesses, Opportunities, and Threats Analysis of Artificial Intelligence and Machine Learning Applications in Radiology
- (2019) Teodoro Martín Noguerol et al. Journal of the American College of Radiology
- Predictive modeling in spine surgery
- (2019) Azeem Tariq Malik et al. Annals of Translational Medicine
- Diagnosis of disc bulge and disc desiccation in lumbar MRI using concatenated shape and texture features with random forest classifier
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- The exploration of feature extraction and machine learning for predicting bone density from simple spine X-ray images in a Korean population
- (2019) Sangwoo Lee et al. SKELETAL RADIOLOGY
- Generative adversarial network in medical imaging: A review
- (2019) Xin Yi et al. MEDICAL IMAGE ANALYSIS
- Compressed Sensing MRI Reconstruction Using a Generative Adversarial Network With a Cyclic Loss
- (2018) Tran Minh Quan et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Low-Dose CT Image Denoising Using a Generative Adversarial Network With Wasserstein Distance and Perceptual Loss
- (2018) Qingsong Yang et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
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- Feasibility and Accuracy of Thoracolumbar Minimally Invasive Pedicle Screw Placement With Augmented Reality Navigation Technology
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- Spine-GAN: Semantic segmentation of multiple spinal structures
- (2018) Zhongyi Han et al. MEDICAL IMAGE ANALYSIS
- Pedicle Screw Placement Using Augmented Reality Surgical Navigation with Intraoperative 3D Imaging
- (2018) Adrian Elmi Terander et al. SPINE
- Vertebral body insufficiency fractures: detection of vertebrae at risk on standard CT images using texture analysis and machine learning
- (2018) Urs J. Muehlematter et al. EUROPEAN RADIOLOGY
- Generative Adversarial Network for Medical Images (MI-GAN)
- (2018) Talha Iqbal et al. JOURNAL OF MEDICAL SYSTEMS
- Dermatologist-level classification of skin cancer with deep neural networks
- (2017) Andre Esteva et al. NATURE
- Vertebral Body Compression Fractures and Bone Density: Automated Detection and Classification on CT Images
- (2017) Joseph E. Burns et al. RADIOLOGY
- Intervertebral disc classification by its degree of degeneration from T2-weighted magnetic resonance images
- (2016) Isaac Castro-Mateos et al. EUROPEAN SPINE JOURNAL
- Semiautomatic computer-aided classification of degenerative lumbar spine disease in magnetic resonance imaging
- (2015) Silvia Ruiz-España et al. COMPUTERS IN BIOLOGY AND MEDICINE
- Monitoring for idiopathic scoliosis curve progression using surface topography asymmetry analysis of the torso in adolescents
- (2015) Amin Komeili et al. Spine Journal
- MR-Guided Vertebroplasty With Augmented Reality Image Overlay Navigation
- (2014) Jan Fritz et al. CARDIOVASCULAR AND INTERVENTIONAL RADIOLOGY
- Robust Detection and Segmentation for Diagnosis of Vertebral Diseases Using Routine MR Images
- (2014) Dženan Zukić et al. COMPUTER GRAPHICS FORUM
- Computer aided diagnosis of degenerative intervertebral disc diseases from lumbar MR images
- (2014) Ayse Betul Oktay et al. COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
- Measuring procedures to determine the Cobb angle in idiopathic scoliosis: a systematic review
- (2013) S. Langensiepen et al. EUROPEAN SPINE JOURNAL
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- (2013) Yuichiro Abe et al. JOURNAL OF NEUROSURGERY-SPINE
- Assessing fracture risk using gradient boosting machine (GBM) models
- (2012) Elizabeth J Atkinson et al. JOURNAL OF BONE AND MINERAL RESEARCH
- Compression fracture diagnosis in lumbar: a clinical CAD system
- (2012) Samah Al-Helo et al. International Journal of Computer Assisted Radiology and Surgery
- Atlas-Based Segmentation of Degenerated Lumbar Intervertebral Discs From MR Images of the Spine
- (2009) S.K. Michopoulou et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
- Automatic Cobb Measurement of Scoliosis Based on Fuzzy Hough Transform with Vertebral Shape Prior
- (2008) Junhua Zhang et al. JOURNAL OF DIGITAL IMAGING
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