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Lumbar Vertebrae

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Deep learning-based detection of lumbar spinal canal stenosis using convolutional neural networks.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Lumbar spinal canal stenosis (LSCS) is the most common spinal degenerative disorder in elderly people and usually first seen by primary care physicians or orthopedic surgeons who are not spine surgery specialists. Magnetic resonan...

Deep learning reconstruction for lumbar spine MRI acceleration: a prospective study.

European radiology experimental
BACKGROUND: We compared magnetic resonance imaging (MRI) turbo spin-echo images reconstructed using a deep learning technique (TSE-DL) with standard turbo spin-echo (TSE-SD) images of the lumbar spine regarding image quality and detection performance...

A microdiscectomy surgical video annotation framework for supervised machine learning applications.

International journal of computer assisted radiology and surgery
PURPOSE: Lumbar discectomy is among the most common spine procedures in the US, with 300,000 procedures performed each year. Like other surgical procedures, this procedure is not excluded from potential complications. This paper presents a video anno...

Policy Learning for Actively Labeled Sample Selection on Lumbar Semi-supervised Classification.

Journal of imaging informatics in medicine
Large labeled data bring significant performance improvement, but acquiring labeled medical data is particularly challenging due to the laborious, time-consuming, and medically qualified annotation. Semi-supervised learning has been employed to lever...

Deep learning application of vertebral compression fracture detection using mask R-CNN.

Scientific reports
Vertebral compression fractures (VCFs) of the thoracolumbar spine are commonly caused by osteoporosis or result from traumatic events. Early diagnosis of vertebral compression fractures can prevent further damage to patients. When assessing these fra...

Super-resolution deep learning reconstruction approach for enhanced visualization in lumbar spine MR bone imaging.

European journal of radiology
OBJECTIVES: This study aims to assess the effectiveness of super-resolution deep-learning-based reconstruction (SR-DLR), which leverages k-space data, on the image quality of lumbar spine magnetic resonance (MR) bone imaging using a 3D multi-echo in-...

SymTC: A symbiotic Transformer-CNN net for instance segmentation of lumbar spine MRI.

Computers in biology and medicine
Intervertebral disc disease, a prevalent ailment, frequently leads to intermittent or persistent low back pain, and diagnosing and assessing of this disease rely on accurate measurement of vertebral bone and intervertebral disc geometries from lumbar...