AIMC Topic: Spine

Clear Filters Showing 131 to 140 of 267 articles

Automatic recognition of whole-spine sagittal alignment and curvature analysis through a deep learning technique.

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: Artificial intelligence based on deep learning (DL) approaches enables the automatic recognition of anatomic landmarks and subsequent estimation of various spinopelvic parameters. The locations of inflection points (IPs) and apices (APs) in ...

Study on Automatic Multi-Classification of Spine Based on Deep Learning and Postoperative Infection Screening.

Journal of healthcare engineering
The preoperative qualitative and hierarchical diagnosis of intervertebral foramen stenosis is very important for clinicians to explore the effect of multimodal analgesia nursing on pain control after spinal fusion and to formulate treatment strategie...

Localization and Edge-Based Segmentation of Lumbar Spine Vertebrae to Identify the Deformities Using Deep Learning Models.

Sensors (Basel, Switzerland)
The lumbar spine plays a very important role in our load transfer and mobility. Vertebrae localization and segmentation are useful in detecting spinal deformities and fractures. Understanding of automated medical imagery is of main importance to help...

Deep learning-based high-accuracy quantitation for lumbar intervertebral disc degeneration from MRI.

Nature communications
To help doctors and patients evaluate lumbar intervertebral disc degeneration (IVDD) accurately and efficiently, we propose a segmentation network and a quantitation method for IVDD from T2MRI. A semantic segmentation network (BianqueNet) composed of...

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...