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Spine

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Bony fixation in the era of spinal robotics: A systematic review and meta-analysis.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
BACKGROUND: Accurate spinal screw placement in spinal instrumentation is of utmost importance to avoid injury to surrounding neurovascular structures. This study was performed to investigate differences in accuracy, operating room time, length of sta...

Verte-Box: A Novel Convolutional Neural Network for Fully Automatic Segmentation of Vertebrae in CT Image.

Tomography (Ann Arbor, Mich.)
Due to the complex shape of the vertebrae and the background containing a lot of interference information, it is difficult to accurately segment the vertebrae from the computed tomography (CT) volume by manual segmentation. This paper proposes a conv...

Spine Medical Image Segmentation Based on Deep Learning.

Journal of healthcare engineering
The aim was to further explore the clinical value of deep learning algorithm in the field of spinal medical image segmentation, and this study designed an improved U-shaped network (BN-U-Net) algorithm and applied it to the spinal MRI medical image s...

Robotic navigation in spine surgery: Where are we now and where are we going?

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Robotic navigation is a new and rapidly emerging niche within minimally invasive spine surgery. The robotic arms-race began in 2004 and has resulted in no less than four major robotic surgical adjuncts. Current Food and Drug Administration (FDA)-appr...

Generation of Vertebra Micro-CT-like Image from MDCT: A Deep-Learning-Based Image Enhancement Approach.

Tomography (Ann Arbor, Mich.)
This paper proposes a deep-learning-based image enhancement approach that can generate high-resolution micro-CT-like images from multidetector computed tomography (MDCT). A total of 12,500 MDCT and micro-CT image pairs were obtained from 25 vertebral...

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...