Research: Automatic calculation of cervical spine parameters using deep learning
Researchers at the Schulthess Clinic have co-authored a study that examines a model that allows for more accurate, automatic measurement of spinal parameters during X-rays. The model is based on deep learning and supports surgeons in particular in the diagnosis of adjacent segment disease.
The scientific work carried out by the Teaching, Research and Development department supports the clinic’s departments and thus helps improve patient care.
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