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Spine

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Automatic Cobb angle measurement method based on vertebra segmentation by deep learning.

Medical & biological engineering & computing
The accuracy of the Cobb measurement is essential for the diagnosis and treatment of scoliosis. Manual measurement is however influenced by the observer variability hence affecting progression evaluation. In this paper, we propose a fully automatic C...

Vertebrae Labeling via End-to-End Integral Regression Localization and Multi-Label Classification Network.

IEEE transactions on neural networks and learning systems
Accurate identification and localization of the vertebrae in CT scans is a critical and standard pre-processing step for clinical spinal diagnosis and treatment. Existing methods are mainly based on the integration of multiple neural networks, and mo...

Development of a Robotic Spine Surgery Program: Rationale, Strategy, Challenges, and Monitoring of Outcomes After Implementation.

The Journal of bone and joint surgery. American volume
Surgical robots were invented in the 1980s, and since then, robotic-assisted surgery has become commonplace. In the field of spine surgery, robotic assistance is utilized mainly to place pedicle screws, and multiple studies have demonstrated that rob...

Using EMG signals to assess proximity of instruments to nerve roots during robot-assisted spinal surgery.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Detecting neural threats using electromyography (EMG) has gained recognition in the field of spinal surgery. To provide an efficient approach to detect neural threats during the operation of the spinal surgery robot, an automated method b...

Toward an artificial intelligence-assisted framework for reconstructing the digital twin of vertebra and predicting its fracture response.

International journal for numerical methods in biomedical engineering
This article presents an effort toward building an artificial intelligence (AI) assisted framework, coined ReconGAN, for creating a realistic digital twin of the human vertebra and predicting the risk of vertebral fracture (VF). ReconGAN consists of ...

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...