Spinopelvic measurements of sagittal balance with deep learning: systematic review and critical evaluation.

Journal: 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

Published Date: Mar 12, 2022

Abstract

PURPOSE: To summarize and critically evaluate the existing studies for spinopelvic measurements of sagittal balance that are based on deep learning (DL).

Authors

Tomaž Vrtovec

Laboratory of Imaging Technologies, Faculty of Electrical Engineering, University of Ljubljana, Tržaška Cesta 25, 1000, Ljubljana, Slovenia. tomaz.vrtovec@fe.uni-lj.si.
Bulat Ibragimov

Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California, 94305, USA.

Keywords

Cross-Sectional Studies Deep Learning Humans Lumbar Vertebrae Lumbosacral Region Pelvis Radiography

External Resources

View on PubMed Access via DOI PubMed (35278146)

Spinopelvic measurements of sagittal balance with deep learning: systematic review and critical evaluation.

Abstract

Authors

Keywords

External Resources

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