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Automatic Spine Segmentation and Parameter Measurement for Radiological Analysis of Whole-Spine Lateral Radiographs Using Deep Learning and Computer Vision.

Journal of digital imaging
Radiographic examination is essential for diagnosing spinal disorders, and the measurement of spino-pelvic parameters provides important information for the diagnosis and treatment planning of spinal sagittal deformities. While manual measurement met...

Robotic-navigated assistance in spine surgery.

The bone & joint journal
The aim of this study was to assess the accuracy of pedicle screw placement, as well as intraoperative factors, radiation exposure, and complication rates in adult patients with degenerative disorders of the thoracic and lumbar spines who have underg...

A deep learning-based technique for the diagnosis of epidural spinal cord compression on thoracolumbar CT.

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: To develop a deep learning (DL) model for epidural spinal cord compression (ESCC) on CT, which will aid earlier ESCC diagnosis for less experienced clinicians.

Lumbar spine segmentation method based on deep learning.

Journal of applied clinical medical physics
Aiming at the difficulties of lumbar vertebrae segmentation in computed tomography (CT) images, we propose an automatic lumbar vertebrae segmentation method based on deep learning. The method mainly includes two parts: lumbar vertebra positioning and...

Robotic navigation during spine surgery: an update of literature.

Expert review of medical devices
INTRODUCTION: The application of robotic navigation during spine surgery has advanced rapidly over the past two decades, especially in the last 5 years. Robotic systems in spine surgery may offer potential advantages for both patients and surgeons. T...

Automatic deep learning-based assessment of spinopelvic coronal and sagittal alignment.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to evaluate an artificial intelligence (AI) solution for estimating coronal and sagittal spinopelvic alignment on conventional uniplanar two-dimensional whole-spine radiograph.

Deep Neural Networks-Based Age Estimation of Cadavers Using CT Imaging of Vertebrae.

International journal of environmental research and public health
Although age estimation upon death is important in the identification of unknown cadavers for forensic scientists, to the best of our knowledge, no study has examined the utility of deep neural network (DNN) models for age estimation among cadavers. ...

Spinal disease diagnosis assistant based on MRI images using deep transfer learning methods.

Frontiers in public health
INTRODUCTION: In light of the potential problems of missed diagnosis and misdiagnosis in the diagnosis of spinal diseases caused by experience differences and fatigue, this paper investigates the use of artificial intelligence technology for auxiliar...