Can pathoanatomical pathways of degeneration in lumbar motion segments be identified by clustering MRI findings
Background: Magnetic Resonance Imaging (MRI) is the gold standard for detailed visualisation of spinal pathological and degenerative processes, but the prevailing view is that such imaging findings have little or no clinical relevance for low back pain. This is because these findings appear to have...
| Main Authors: | Jensen, R., Jensen, T., Kjaer, P., Kent, Peter |
|---|---|
| Format: | Journal Article |
| Published: |
Biomed Central Ltd
2013
|
| Online Access: | http://hdl.handle.net/20.500.11937/54894 |
Similar Items
Degenerative Pathways of Lumbar Motion Segments--A Comparison in Two Samples of Patients with Persistent Low Back Pain
by: Jensen, R., et al.
Published: (2016)
by: Jensen, R., et al.
Published: (2016)
The association between subgroups of MRI findings identified with latent class analysis and low back pain in 40-year old Danes
by: Jensen, R., et al.
Published: (2018)
by: Jensen, R., et al.
Published: (2018)
Is the Number of Different MRI Findings More Strongly Associated with Low Back Pain Than Single MRI Findings?
by: Hancock, M., et al.
Published: (2017)
by: Hancock, M., et al.
Published: (2017)
Inexperienced clinicians can extract pathoanatomic information from MRI narrative reports with high reproducibility for use in research/quality assurance
by: Kent, P., et al.
Published: (2011)
by: Kent, P., et al.
Published: (2011)
A comparison of three clustering methods for finding subgroups in MRI, SMS or clinical data: SPSS TwoStep Cluster analysis, Latent Gold and SNOB
by: Kent, Peter, et al.
Published: (2014)
by: Kent, Peter, et al.
Published: (2014)
Do MRI findings identify patients with chronic low back pain and Modic changes who respond best to rest or exercise: A subgroup analysis of a randomised controlled trial
by: Jensen, R., et al.
Published: (2015)
by: Jensen, R., et al.
Published: (2015)
Development of ground truth data for automatic lumbar spine MRI image segmentation
by: Natalia, Friska, et al.
Published: (2019)
by: Natalia, Friska, et al.
Published: (2019)
Clinically acceptable agreement between the ViMove wireless motion sensor system and the Vicon motion capture system when measuring lumbar motion in flexion/extension and lateral flexion
by: Mjøsund, H., et al.
Published: (2017)
by: Mjøsund, H., et al.
Published: (2017)
Identification of subgroups of inflammatory and degenerative MRI findings in the axial skeleton: A latent class analysis of 1,037 patients with persistent low back pain
by: Arnbak, B., et al.
Published: (2016)
by: Arnbak, B., et al.
Published: (2016)
Segmentation of lumbar spine MRI images for stenosis detection using patch-based pixel classification neural network
by: Al Kafri, Ala S, et al.
Published: (2018)
by: Al Kafri, Ala S, et al.
Published: (2018)
The lumbar spine of the young cricket fast bowler: An MRI study
by: Crewe, H., et al.
Published: (2012)
by: Crewe, H., et al.
Published: (2012)
Do MRI findings identify patients with low back pain or sciatica who respond better to particular interventions? A systematic review
by: Steffens, D., et al.
Published: (2016)
by: Steffens, D., et al.
Published: (2016)
A conceptual model of compensation/decompensation in lumbar segmental instability
by: Barz, T., et al.
Published: (2014)
by: Barz, T., et al.
Published: (2014)
Motion correction in high-field MRI
by: Sulikowska, Aleksandra
Published: (2016)
by: Sulikowska, Aleksandra
Published: (2016)
Upper and lower lumbar segments move differently during sit-to-stand
by: Parkinson, Stephanie, et al.
Published: (2013)
by: Parkinson, Stephanie, et al.
Published: (2013)
MRI evaluation of the lumbar spine ligamentum flavum & its contribution to degenerative spinal stenosis
by: Lian, Teh Hak
Published: (2018)
by: Lian, Teh Hak
Published: (2018)
Review of brain MRI image segmentation methods
by: Balafar, Mohammad Ali, et al.
Published: (2010)
by: Balafar, Mohammad Ali, et al.
Published: (2010)
Rate of lumbar paravertebral muscle fat infiltration versus spinal degeneration in asymptomatic populations: an age-aggregated cross-sectional simulation study.
by: Crawford, R., et al.
Published: (2016)
by: Crawford, R., et al.
Published: (2016)
Features extraction based on fuzzy clustering and segmentation onto the motion region for medium field surveillance application
by: Maliki, Mohamad Nansah, et al.
Published: (2004)
by: Maliki, Mohamad Nansah, et al.
Published: (2004)
Normative MRI, ultrasound and muscle functional MRI findings in the forearms of asymptomatic elite rowers
by: Drew, M., et al.
Published: (2016)
by: Drew, M., et al.
Published: (2016)
Motion correction for MRI using external tracking devices
by: Smith, James
Published: (2019)
by: Smith, James
Published: (2019)
Identifying clinical course patterns in SMS data using cluster analysis
by: Kent, Peter, et al.
Published: (2012)
by: Kent, Peter, et al.
Published: (2012)
Segmentation of MRI brain images using statistical approaches
by: Balafar, Mohammad Ali
Published: (2011)
by: Balafar, Mohammad Ali
Published: (2011)
Customer segmentation on clustering algorithms
by: Toh, Wei Xuan
Published: (2023)
by: Toh, Wei Xuan
Published: (2023)
Lumbar MRI abnormalities and muscle morphology, trunk kinematics and lower back injury in professional fast bowlers in cricket
by: Ranson, Craig A
Published: (2007)
by: Ranson, Craig A
Published: (2007)
Development of morphological technique for segmentation of anatomical objects in abdominal MRI
by: Sarker, S. Z., et al.
Published: (2008)
by: Sarker, S. Z., et al.
Published: (2008)
MRI Human Brain Segmentation / Classification Using Bayesian Techniques
by: Safa, Soodabeh
Published: (2010)
by: Safa, Soodabeh
Published: (2010)
Why and how back pain interventions work: What can we do to find out?
by: Mansell, G., et al.
Published: (2013)
by: Mansell, G., et al.
Published: (2013)
Studying neural selectivity for motion using high-field fMRI
by: Beckett, Alexander
Published: (2013)
by: Beckett, Alexander
Published: (2013)
Assessment of motion of colonic contents in the human colon using MRI tagging
by: Pritchard, Susan E., et al.
Published: (2017)
by: Pritchard, Susan E., et al.
Published: (2017)
Exploring the origins of EEG motion artefacts during simultaneous fMRI acquisition: implications for motion artefact correction
by: Spencer, Glyn S., et al.
Published: (2018)
by: Spencer, Glyn S., et al.
Published: (2018)
Segmentation methods for MRI human spine images using thresholding approaches
by: Nor Aqlina Abdul Halim,, et al.
Published: (2022)
by: Nor Aqlina Abdul Halim,, et al.
Published: (2022)
Trainable model for segmenting and identifying Nasopharyngeal carcinoma
by: Mohammed, Mazin Abed, et al.
Published: (2018)
by: Mohammed, Mazin Abed, et al.
Published: (2018)
Changes in adolescent intervertebral discs, end plates and bone marrow of lumbar spine in idiopathic thoracic scoliosis an mri based study
by: Kassim, Ahmad Fauzey
Published: (2010)
by: Kassim, Ahmad Fauzey
Published: (2010)
Changes in adolescent intervertebral discs, end plates and
bone marrow of lumbar spine in idiopatidc thoracic scoliosis
an mri based study
by: Ahmad Fauzey, Kassim
Published: (2010)
by: Ahmad Fauzey, Kassim
Published: (2010)
Lumbar support system
by: Salit, Mohd Sapuan, et al.
Published: (2012)
by: Salit, Mohd Sapuan, et al.
Published: (2012)
Ergonomic lumbar support
by: Karuppiah, Karmegam, et al.
Published: (2013)
by: Karuppiah, Karmegam, et al.
Published: (2013)
Compression of Patient Monitoring Video Using Motion Segmentation Technique
by: Shyamsunder, R., et al.
Published: (2007)
by: Shyamsunder, R., et al.
Published: (2007)
Identifying Clusters Of Users In Twitter Dataset
by: Heidarian, Arash
Published: (2011)
by: Heidarian, Arash
Published: (2011)
Brain white and gray matter anatomy of MRI segmentation based on tissue evaluation
by: Salih, Qussay Abbas, et al.
Published: (2005)
by: Salih, Qussay Abbas, et al.
Published: (2005)
Similar Items
-
Degenerative Pathways of Lumbar Motion Segments--A Comparison in Two Samples of Patients with Persistent Low Back Pain
by: Jensen, R., et al.
Published: (2016) -
The association between subgroups of MRI findings identified with latent class analysis and low back pain in 40-year old Danes
by: Jensen, R., et al.
Published: (2018) -
Is the Number of Different MRI Findings More Strongly Associated with Low Back Pain Than Single MRI Findings?
by: Hancock, M., et al.
Published: (2017) -
Inexperienced clinicians can extract pathoanatomic information from MRI narrative reports with high reproducibility for use in research/quality assurance
by: Kent, P., et al.
Published: (2011) -
A comparison of three clustering methods for finding subgroups in MRI, SMS or clinical data: SPSS TwoStep Cluster analysis, Latent Gold and SNOB
by: Kent, Peter, et al.
Published: (2014)