ArticleMagnetic resonance in medicine2020
Lumbar intervertebral disc characterization through quantitative MRI analysis: An automatic voxel-based relaxometry approach.
Article in Magnetic resonance in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 4 of them syntheses that pooled it.
What it found
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Who cites it
15 citing papers in PubMed, 4 syntheses or guidelines pooled it, 24 citations in OpenAlex.
- Deep learning for the diagnosis of lumbar disc herniation: a systematic review and meta-analysis.BMC medical imaging · 2026Pooled it
- The Impact of Exercise on Intervertebral Disc Health: A Systematic Review and Meta-Analysis.Sports medicine (Auckland, N.Z.) · 2026Pooled it
- Deep learning assisted segmentation of the lumbar intervertebral disc: a systematic review and meta-analysis.Journal of orthopaedic surgery and research · 2024Pooled it
- Artificial Intelligence and Computer Vision in Low Back Pain: A Systematic Review.International journal of environmental research and public health · 2021Pooled it
- HRNet-ACAP-Offset: a novel framework for localizing posterior edge landmark points in 3D intervertebral disc MRI.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 · 2026Article
- Bibliometric analysis of the application of artificial intelligence in orthopedic imaging.Quantitative imaging in medicine and surgery · 2025Article
- Characterization of Normal and Degenerative Discovertebral Complexes Using Qualitative and Quantitative Magnetic Resonance Imaging at 4.7T: Longitudinal Evaluation of Immature and Mature Rats.Bioengineering (Basel, Switzerland) · 2025Article
- Deep Learning for Multi-Tissue Segmentation and Fully Automatic Personalized Biomechanical Models from BACPAC Clinical Lumbar Spine MRI.Pain medicine (Malden, Mass.) · 2023Article
- Region of interest-specific loss functions improve TScientific reports · 2022Article
- Deep Learning and Its Application to Function Approximation for MR in Medicine: An Overview.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2022Review
- The contributions of cartilage endplate composition and vertebral bone marrow fat to intervertebral disc degeneration in patients with chronic low back pain.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 · 2022Observational
- Current development and prospects of deep learning in spine image analysis: a literature review.Quantitative imaging in medicine and surgery · 2022Review
- Increasing BMI increases lumbar intervertebral disc deformation following a treadmill walking stress test.Journal of biomechanics · 2021Article
- Lumbar intervertebral disc characterization through quantitative MRI analysis: An automatic voxel-based relaxometry approach.Magnetic resonance in medicine · 2020Article
- A Review on the Use of Artificial Intelligence in Spinal Diseases.Asian spine journal · 2020Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
purposeTo develop an automated pipeline based on convolutional neural networks to segment lumbar intervertebral discs and characterize their biochemical composition using voxel-based relaxometry, and establish local associations with clinical measures of disability, muscle changes, and other symptoms of lower back pain.
methodsThis work proposes a new methodology using MRI (n = 31, across the spectrum of disc degeneration) that combines deep learning-based segmentation, atlas-based registration, and statistical parametric mapping for voxel-based analysis of T
resultsAcross degenerative grades, the segmentation algorithm produced accurate, high-confidence segmentations of the lumbar discs in two independent data sets. Manually and automatically extracted mean disc T
conclusionThis work presented a scalable pipeline for fast, automated assessment of disc relaxation times, and voxel-based relaxometry that overcomes limitations of current region of interest-based analysis methods and may enable greater insights and associations between disc degeneration, disability, and lower back pain.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.