Computer vision is superior to surgeons in identifying spinal implants, shows study

Identifying previously placed spinal hardware can be difficult and time consuming when a patient needs revision surgery. Detailed information on the implant model and type are often lacking when patients are referred elsewhere or may be missing in the surgical notes. To overcome this challenge, researchers developed a computer vision machine learning approach that more accurately and efficiently identifies previously placed thoracolumbar instrumentation.