Automatic Scan Planning for Magnetic Resonance Imaging of the Knee Joint

Bauer, Stefan; Ritacco, Lucas E.; Boesch, Chris; Nolte, Lutz-P.; Reyes, Mauricio (2012). Automatic Scan Planning for Magnetic Resonance Imaging of the Knee Joint. Annals of biomedical engineering, 40(9), pp. 2033-42. Cambridge: Springer US; http://www.springer-ny.com 10.1007/s10439-012-0552-1

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Automatic scan planning for magnetic resonance imaging of the knee aims at defining an oriented bounding box around the knee joint from sparse scout images in order to choose the optimal field of view for the diagnostic images and limit acquisition time. We propose a fast and fully automatic method to perform this task based on the standard clinical scout imaging protocol. The method is based on sequential Chamfer matching of 2D scout feature images with a three-dimensional mean model of femur and tibia. Subsequently, the joint plane separating femur and tibia, which contains both menisci, can be automatically detected using an information-augmented active shape model on the diagnostic images. This can assist the clinicians in quickly defining slices with standardized and reproducible orientation, thus increasing diagnostic accuracy and also comparability of serial examinations. The method has been evaluated on 42 knee MR images. It has the potential to be incorporated into existing systems because it does not change the current acquisition protocol.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute for Surgical Technology & Biomechanics ISTB [discontinued]
04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic, Interventional and Paediatric Radiology > DCR Magnetic Resonance Spectroscopy and Methodology (AMSM)

UniBE Contributor:

Bauer, Stefan; Bösch, Christoph Hans; Nolte, Lutz-Peter and Reyes, Mauricio

Subjects:

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

ISSN:

0090-6964

Publisher:

Springer US; http://www.springer-ny.com

Language:

English

Submitter:

Factscience Import

Date Deposited:

04 Oct 2013 14:22

Last Modified:

26 Feb 2020 12:01

Publisher DOI:

10.1007/s10439-012-0552-1

PubMed ID:

22441666

Web of Science ID:

000307400900017

BORIS DOI:

10.7892/boris.7646

URI:

https://boris.unibe.ch/id/eprint/7646 (FactScience: 212956)

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