Paper
29 August 2016 Atlas-based segmentation of neck muscles from MRI for the characterisation of Whiplash Associated Disorder
Abdulla Al Suman, Nargis Aktar, Md. Asikuzzaman, Alexandra Louise Webb, Diana M. Perriman, Mark R. Pickering
Author Affiliations +
Proceedings Volume 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016); 100334L (2016) https://doi.org/10.1117/12.2243754
Event: Eighth International Conference on Digital Image Processing (ICDIP 2016), 2016, Chengu, China
Abstract
Whiplash-associated disorder (WAD) is a commonly occurring injury that often results from neck trauma suffered in car accidents. However the cause of the condition is still unknown and there is no definitive clinical test for the presence of the condition. Researchers have begun to analyze the size of neck muscles and the presence of fatty infiltrates to help understand WAD. However this analysis requires a high precision delineation of neck muscles which is very challenging due to a lack of distinctive features in neck magnetic resonance imaging (MRI). This paper presents a novel atlas-based neck muscle segmentation method which employs discrete cosine-based elastic registration with affine initialization. Our algorithm shows promising results based on clinical data with an average Dice similarity coefficient (DSC) of 0.84±0.0004.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Abdulla Al Suman, Nargis Aktar, Md. Asikuzzaman, Alexandra Louise Webb, Diana M. Perriman, and Mark R. Pickering "Atlas-based segmentation of neck muscles from MRI for the characterisation of Whiplash Associated Disorder", Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100334L (29 August 2016); https://doi.org/10.1117/12.2243754
Lens.org Logo
CITATIONS
Cited by 4 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Neck

Image segmentation

Magnetic resonance imaging

Image registration

Analytical research

Tongue

Injuries

RELATED CONTENT


Back to Top