Automated Intervertebral Disc Detection from Low Resolution, Sparse MRI Images for the Planning of Scan Geometries

Dong, Xiao; Lu, Huanxiang; Sakurai, Yasuo; Yamagata, Hitoshi; Zheng, Guoyan; Reyes, Mauricio (2010). Automated Intervertebral Disc Detection from Low Resolution, Sparse MRI Images for the Planning of Scan Geometries. In: Wang, Fei; Yan, Pingkun; Suzuki, Kenji; Shen, Dinggang (eds.) Machine learning in Medical Imaging (MLMI) - MICCAI 2010 Workshop. Lecture Notes in Computer Science: Vol. 6357 (pp. 10-17). Berlin: Springer 10.1007/978-3-642-15948-0_2

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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.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

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

UniBE Contributor:

Dong, Xiao; Lu, Huanxiang; Zheng, Guoyan and Reyes, Mauricio

Subjects:

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

ISSN:

0302-9743

ISBN:

978-3-642-15948-0

Series:

Lecture Notes in Computer Science

Publisher:

Springer

Language:

English

Submitter:

Mauricio Antonio Reyes Aguirre

Date Deposited:

04 Oct 2013 14:08

Last Modified:

29 Dec 2014 10:19

Publisher DOI:

10.1007/978-3-642-15948-0_2

Web of Science ID:

000287945800002

BORIS DOI:

10.7892/boris.627

URI:

https://boris.unibe.ch/id/eprint/627 (FactScience: 199887)

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