AIMC Topic: Spinal Stenosis

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Qualitative versus quantitative lumbar spinal stenosis grading by machine learning supported texture analysis-Experience from the LSOS study cohort.

European journal of radiology Feb 19, 2019
PURPOSE: To investigate and compare the reproducibility and accuracy of qualitative ratings and quantitative texture analysis (TA) in detection and grading of lumbar spinal stenosis (LSS) in magnetic resonance imaging (MR) scans of the lumbar spine.
Observer Variation Reference Standards Humans Lumbar Vertebrae Spinal Stenosis Male Machine Learning Outcome Assessment, Health Care Middle Aged Algorithms Cohort Studies Female Magnetic Resonance Imaging Reproducibility of Results Aged Aged, 80 and over
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ISSLS PRIZE IN BIOENGINEERING SCIENCE 2017: Automation of reading of radiological features from magnetic resonance images (MRIs) of the lumbar spine without human intervention is comparable with an expert radiologist.

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 Feb 6, 2017
STUDY DESIGN: Investigation of the automation of radiological features from magnetic resonance images (MRIs) of the lumbar spine.
Neural Networks, Computer Spinal Stenosis Humans Male Intervertebral Disc Degeneration Middle Aged Magnetic Resonance Imaging Spondylolisthesis Intervertebral Disc Radiologists Lumbar Vertebrae Bone Marrow
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Unsupervised boundary delineation of spinal neural foramina using a multi-feature and adaptive spectral segmentation.

Medical image analysis Oct 29, 2016
As a common disease in the elderly, neural foramina stenosis (NFS) brings a significantly negative impact on the quality of life due to its symptoms including pain, disability, fall risk and depression. Accurate boundary delineation is essential to t...
Humans Unsupervised Machine Learning Algorithms Spinal Stenosis Magnetic Resonance Imaging Spinal Canal
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A novel deep learning system for automated diagnosis and grading of lumbar spinal stenosis based on spine MRI: model development and validation.

Neurosurgical focus Jul 1, 2025
OBJECTIVE: The study aimed to develop a single-stage deep learning (DL) screening system for automated binary and multiclass grading of lumbar central stenosis (LCS), lateral recess stenosis (LRS), and lumbar foraminal stenosis (LFS).
Retrospective Studies Female Reproducibility of Results Aged Humans Deep Learning Magnetic Resonance Imaging Lumbar Vertebrae Spinal Stenosis Aged, 80 and over Adult Male Middle Aged
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Performance of Artificial Intelligence in Diagnosing Lumbar Spinal Stenosis: A Systematic Review and Meta-Analysis.

Spine May 15, 2025
STUDY DESIGN: The present study followed the reporting guidelines for systematic reviews and meta-analyses.
Lumbar Vertebrae Spinal Stenosis Humans Artificial Intelligence
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Feasibility of deep learning algorithm in diagnosing lumbar central canal stenosis using abdominal CT.

Skeletal radiology May 1, 2025
OBJECTIVE: To develop a deep learning algorithm for diagnosing lumbar central canal stenosis (LCCS) using abdominal CT (ACT) and lumbar spine CT (LCT).
Humans Algorithms Retrospective Studies Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Lumbar Vertebrae Feasibility Studies Sensitivity and Specificity Spinal Stenosis Male Female Radiography, Abdominal Middle Aged Aged Deep Learning Aged, 80 and over
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Detection of Cervical Foraminal Stenosis from Oblique Radiograph Using Convolutional Neural Network Algorithm.

Yonsei medical journal Jul 1, 2024
PURPOSE: This study was conducted to develop a convolutional neural network (CNN) algorithm that can diagnose cervical foraminal stenosis using oblique radiographs and evaluate its accuracy.
Adult Male Middle Aged ROC Curve Algorithms Female Aged Magnetic Resonance Imaging Radiography Cervical Vertebrae Spinal Stenosis Humans Neural Networks, Computer
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Deep learning-based spinal canal segmentation of computed tomography image for disease diagnosis: A proposed system for spinal stenosis diagnosis.

Medicine May 3, 2024
BACKGROUND: Lumbar disc herniation was regarded as an age-related degenerative disease. Nevertheless, emerging reports highlight a discernible shift, illustrating the prevalence of these conditions among younger individuals.
Image Processing, Computer-Assisted Adult Lumbar Vertebrae Male Spinal Stenosis Middle Aged Humans Intervertebral Disc Displacement Deep Learning Tomography, X-Ray Computed Spinal Canal Female
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Deep-learning reconstruction for the evaluation of lumbar spinal stenosis in computed tomography.

Medicine Jun 9, 2023
To compare the quality and interobserver agreement in the evaluation of lumbar spinal stenosis (LSS) on computed tomography (CT) images between deep-learning reconstruction (DLR) and hybrid iterative reconstruction (hybrid IR). This retrospective stu...
Aged, 80 and over Algorithms Male Radiographic Image Interpretation, Computer-Assisted Humans Middle Aged Spinal Stenosis Retrospective Studies Deep Learning Radiation Dosage Tomography, X-Ray Computed Lumbosacral Region Aged
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Deep Learning Algorithm Trained on Lumbar Magnetic Resonance Imaging to Predict Outcomes of Transforaminal Epidural Steroid Injection for Chronic Lumbosacral Radicular Pain.

Pain physician Nov 1, 2022
BACKGROUND: Transforaminal epidural steroid injections (TFESI) are widely used to alleviate lumbosacral radicular pain. Knowledge of the therapeutic outcomes of TFESI allows clinicians to elucidate therapeutic plans for managing lumbosacral radicular...
Deep Learning Treatment Outcome Magnetic Resonance Imaging Lumbar Vertebrae Injections, Epidural Spinal Stenosis Radiculopathy Humans Steroids Intervertebral Disc Displacement Back Pain
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