Doctor Examines MRI of Lumbar Spine with cookelma | 0:00 Physiotherapist's hands working the lumbar area of a patient who is on the stretcher BlackBoxGuild | 0:00 Man with severe back pain. Lumbar hernia. Nardavar | 0:00 An Orthopedist Talks to an Elderly Woman at the Reception ...
A retrospective study was conducted at four hospitals around China, in which the study population composed of patients who completed lumbar-spine MRI examination between January 1, 2019 and March 30, 2021. Further screening was conducted to exclude IVD herniation, lumbar spondylolisthesis, spine tumors...
The experiments are performed on 1545 axial-view MRI images. Furthermore, two datasets鈥攎ulti-ROI and single-ROI鈥攁re created. For training and testing, an 80:20 ratio of randomly selected labeled datasets is used, with fivefold cross-validation. The results of ...
Sixty sciatic pain patients with LDH as confirmed by MRI will be recruited from outpatients visiting Jaseng Hospital of Korean medicine, which is a spine-specialty hospital designated as such by the Korean Ministry of Health and Welfare (900,000 outpatient cases per year). Advertisements will also...
A study showed that ultrasound-guided MTLIP could improve postoperative pain in lumbar spine surgery.16 Although the optimal analgesic technique for pain management following Tianji robot-assisted lumbar internal fixation has not yet been determined, it is important to validate alternative analgesic ...
The data can be used as a training and test datasets for the development of automatic lumbar muscle and spine segmentation algorithms. These algorithms are highly needed to promote and accelerate the wide spread clinical implementation of quantitative muscle MRI for diagnosis of muscle and vertebral ...
After MRI imaging, spinal cords were dissected from the spine and a transverse (1.5-mm-thick) spinal cord block cut from the injury epicenter and prepared for plastic embedding as previously described [41]. Briefly, dissected tissue blocks were treated with 0.1% osmium tetroxide in 0.1 M non-...
All data were labeled by two spine surgeons using the widely accepted grading system for lumbar spinal stenosis. The training and validation sets were used to annotate the regions of interest by the two spine surgeons. First, a region of interest detection model and a convolutional neural network...
This study aimed to develop an MRI鈥恇ased decision support system for LDH, which evaluates lumbar discs in a reproducible, consistent, and reliable manner. Methods: The research team proposed a system based on machine learning that was trained and tested by a large, manually labeled...
We estimate the model parameters from manually labeled cases (supervised learning).;Then we perform machine-learning based analysis at each localized disc for further diagnosis tasks. Our proposed model investigates degenerative abnormalities and allows the flexibility of adding features depending on the ...