Could automated machine-learned MRI grading aid epidemiological studies of lumbar spinal stenosis? Validation within the Wakayama spine study

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

(2017) Amir Jamaludin et al.   EUROPEAN SPINE JOURNAL

SpineNet: Automated classification and evidence visualization in spinal MRIs

(2017) Amir Jamaludin et al.   MEDICAL IMAGE ANALYSIS

Prevalence of symptomatic lumbar spinal stenosis and its association with physical performance in a population-based cohort in Japan: the Wakayama Spine Study

(2012) Y. Ishimoto et al.   OSTEOARTHRITIS AND CARTILAGE

Quantitative radiologic criteria for the diagnosis of lumbar spinal stenosis: a systematic literature review

(2011) Johann Steurer et al.   BMC MUSCULOSKELETAL DISORDERS

Trends, Major Medical Complications, and Charges Associated With Surgery for Lumbar Spinal Stenosis in Older Adults

(2010) Richard A. Deyo   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Does This Older Adult With Lower Extremity Pain Have the Clinical Syndrome of Lumbar Spinal Stenosis?

(2010) Pradeep Suri et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Qualitative Grading of Severity of Lumbar Spinal Stenosis Based on the Morphology of the Dural Sac on Magnetic Resonance Images

(2010) Constantin Schizas et al.   SPINE

Cohort Profile: Research on Osteoarthritis/Osteoporosis Against Disability study

(2009) N. Yoshimura et al.   INTERNATIONAL JOURNAL OF EPIDEMIOLOGY

Lumbar Spinal Stenosis

(2008) Jeffrey N. Katz et al.   NEW ENGLAND JOURNAL OF MEDICINE

Reliability of Readings of Magnetic Resonance Imaging Features of Lumbar Spinal Stenosis

(2008) Jon D. Lurie et al.   SPINE