AIMC Topic: Spine

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Comparison of manual versus automated measurement of Cobb angle in idiopathic scoliosis based on a deep learning keypoint detection technology.

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
PURPOSE: The present study compared manual and automated measurement of Cobb angle in idiopathic scoliosis based on deep learning keypoint detection technology.

Machine learning techniques demonstrating individual movement patterns of the vertebral column: the fingerprint of spinal motion.

Computer methods in biomechanics and biomedical engineering
Surface topography systems enable the capture of spinal dynamic movement; however, it is unclear whether vertebral dynamics are unique enough to identify individuals. Therefore, in this study, we investigated whether the identification of individuals...

Fully Automated Deep Learning Tool for Sarcopenia Assessment on CT: L1 Versus L3 Vertebral Level Muscle Measurements for Opportunistic Prediction of Adverse Clinical Outcomes.

AJR. American journal of roentgenology
Sarcopenia is associated with adverse clinical outcomes. CT-based skeletal muscle measurements for sarcopenia assessment are most commonly performed at the L3 vertebral level. The purpose of this article is to compare the utility of fully automated...

Precise laminae segmentation based on neural network for robot-assisted decompressive laminectomy.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The decompressive laminectomy is one of the most common operations to treat lumbar spinal stenosis by removing the laminae above the spinal nerve. Recently, an increasing number of robots are deployed during the surgical pro...

LPAQR-Net: Efficient Vertebra Segmentation From Biplanar Whole-Spine Radiographs.

IEEE journal of biomedical and health informatics
Vertebra segmentation from biplanar whole-spine radiographs is highly demanded in the quantitative assessment of scoliosis and the resultant sagittal deformities. However, automatic vertebra segmentation from the radiographs is extremely challenging ...

Artificial intelligence and spine: rise of the machines.

The spine journal : official journal of the North American Spine Society

Automatic classification of medical image modality and anatomical location using convolutional neural network.

PloS one
Modern radiologic images comply with DICOM (digital imaging and communications in medicine) standard, which, upon conversion to other image format, would lose its image detail and information such as patient demographics or type of image modality tha...

Is there a difference between navigated and non-navigated robot cohorts in robot-assisted spine surgery? A multicenter, propensity-matched analysis of 2,800 screws and 372 patients.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Robot-assisted spine surgery continues to rapidly develop as evidenced by the growing literature in recent years. In addition to demonstrating excellent pedicle screw accuracy, early studies have explored the impact of robot-assis...

State-of-the-art reviews predictive modeling in adult spinal deformity: applications of advanced analytics.

Spine deformity
Adult spinal deformity (ASD) is a complex and heterogeneous disease that can severely impact patients' lives. While it is clear that surgical correction can achieve significant improvement of spinopelvic parameters and quality of life measures in adu...

Artificial intelligence for adult spinal deformity: current state and future directions.

The spine journal : official journal of the North American Spine Society
As we experience a technological revolution unlike any other time in history, spinal surgery as a discipline is poised to undergo a dramatic transformation. As enormous amounts of data become digitized and more readily available, medical professional...