Automated 3D Lumbar Intervertebral Disc Segmentation from MRI Data Sets

Dong, Xiao; Zheng, Guoyan (2015). Automated 3D Lumbar Intervertebral Disc Segmentation from MRI Data Sets. In: Yao, J.; Glocker, B.; Klinder, T.; Li, S. (eds.) Recent Advances in Computational Methods and Clinical Applications for Spine Imaging. Lecture Notes in Computational Vision and Biomechanics: Vol. 20 (pp. 131-142). Cham: Springer International Publishing 10.1007/978-3-319-14148-0_12

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This paper proposed an automated 3D lumbar intervertebral disc (IVD) segmentation strategy from MRI data. Starting from two user supplied landmarks, the geometrical parameters of all lumbar vertebral bodies and intervertebral discs are automatically extracted from a mid-sagittal slice using a graphical model based approach. After that, a three-dimensional (3D) variable-radius soft tube model of the lumbar spine column is built to guide the 3D disc segmentation. The disc segmentation is achieved as a multi-kernel diffeomorphic registration between a 3D template of the disc and the observed MRI data. Experiments on 15 patient data sets showed the robustness and the accuracy of the proposed algorithm.

Item Type:

Book Section (Book Chapter)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute for Surgical Technology & Biomechanics ISTB [discontinued]

Graduate School:

Graduate School for Cellular and Biomedical Sciences (GCB)

UniBE Contributor:

Zheng, Guoyan

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health
600 Technology > 620 Engineering

ISBN:

978-3-319-14147-3

Series:

Lecture Notes in Computational Vision and Biomechanics

Publisher:

Springer International Publishing

Language:

English

Submitter:

Guoyan Zheng

Date Deposited:

07 May 2015 08:45

Last Modified:

26 Apr 2017 02:29

Publisher DOI:

10.1007/978-3-319-14148-0_12

BORIS DOI:

10.7892/boris.67981

URI:

https://boris.unibe.ch/id/eprint/67981

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