Automatic identification of three-dimensional morphometric features of vertebrae

ABSTRACT

To avoid variability and subjectivity in the measurement of vertebral morphometric features, we developed a system to automatically identify their landmarks and extract three-dimensional (3D) features. On a 3D vertebral model reconstructed from computerised tomography (CT) scans, the symmetry plane was identified. Based on this plane, the coronal planes and the reference frame were determined. A total of 12 morphometric features and 14 landmarks were identified based on these derived planes and frames. The identification generated by the system was validated according to the manual annotations of two orthopaedic experts. The automatically identified landmarks and features agreed with the manual identifications, with average differences less of than 1.91 mm and 1.6 for the landmarks and features, respectively. Paired t-tests showed no statistically significant differences between auto-user variability and inter-user variability in the identified landmarks or the extracted features (p > 0.05). These results indicated that the proposed approach can be an aid in the task of measuring vertebral morphometric features in medicine, anthropological, and forensic investigations.

KEYWORDS:

• Vertebra
• morphometric features
• automatic identification
• three-dimensional model

Acknowledgments

This work was supported by the National Natural Science Foundation of China under grant No. 62063034.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [62063034].

Notes on contributors

Junhua Zhang

Junhua Zhang received the B.Sc. and M.Sc. degrees in electronic engineering from Yunnan University, Kunming, China in 1999 and 2002, and Ph.D. degree in biomedical engineering from Fudan University, Shanghai, China, in 2007. During 2007 to 2008, she was a Postdoctoral Research Fellow with the Department of Radiology and Diagnostic Imaging at University of Alberta, Edmonton, Canada. In August 2008, she went back to Department of Electronic Engineering at Yunnan University as an assistant professor. She was then promoted to a full professor in November, 2015. Her research interests are in medical image processing and pattern recognition.

Bo Li

Bo Li received the B.Sc and M.Sc. degrees in Electronic Engineering from Inner Mongolia University of Science & Technology and Yunnan University, China in 2017 and 2021, respectively. He is pursuing his Ph.D. degree with the major of Information and Communication Engineering at Yunnan University. His research interests are in medical image processing and pattern recognition.

Hongjian Li

Hongjian Li received the M.B. degree at West China University of Medical Sciences, Chengdu, China in 1992 and C.M. degree at Kunming Medical University, Kunming, China in 2010. He joined the Orthopedics Department at the First People’s Hospital in 1993. He was then promoted to a Chief of Surgery in August 2017. His research interests are in the treatment of spine problems and osteoporosis.

Shuai Zhang

Shuai Zhang received the B.Sc degree in Electronic Engineering from Shanghai Second Polytechnic University, China in 2019. He is pursuing his M.Sc. degree with the major of Electronic Engineering at Yunnan University. His research interests are in medical image processing and pattern recognition.

Wentao Yu

Wentao Yu received the B.Sc degree in Electronic Engineering from Jinggangshan University, China in 2019. He is pursuing his M.Sc. degree with the major of Electronic Engineering at Yunnan University. His research interests are in medical image processing and pattern recognition.