Automated intervertebral disc detection from low resolution, sparse MRI images for the planning of scan geometries

Authors:
Xiao Dong;Huanxiang Lu;Yasuo Sakurai;Hitoshi Yamagata;Guoyan Zheng;Mauricio Reyes
Affiliations:
Institute for Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland;Institute for Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland;Toshiba Medical Systems Corporation, Otawara, Japan;Toshiba Medical Systems Corporation, Otawara, Japan;Institute for Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland;Institute for Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland
Venue:
MLMI'10 Proceedings of the First international conference on Machine learning in medical imaging
Year:
2010

Citing 4
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Abstract

Robust and accurate identification of intervertebral discs from low resolution, sparse MRI scans is essential for the automated scan planning of the MRI spine scan. This paper presents a graphical model based solution for the detection of both the positions and orientations of intervertebral discs from low resolution, sparse MRI scans. Compared with the existing graphical model based methods, the proposed method does not need a training process using training data and it also has the capability to automatically determine the number of vertebrae visible in the image. Experiments on 25 low resolution, sparse spine MRI data sets verified its performance.