TY  - JOUR
PY  - 2014//
TI  - A machine learning approach for specification of spinal cord injuries using fractional anisotropy values obtained from diffusion tensor images
JO  - Computational and mathematical methods in medicine
A1  - Tay, Bunheang
A1  - Hyun, Jung Keun
A1  - Oh, Sejong
SP  - e276589
EP  - e276589
VL  - 2014
IS  - 
N2  - Diffusion Tensor Imaging (DTI) uses in vivo images that describe extracellular structures by measuring the diffusion of water molecules. These images capture axonal movement and orientation using echo-planar imaging and provide critical information for evaluating lesions and structural damage in the central nervous system. This information can be used for prediction of Spinal Cord Injuries (SCIs) and for assessment of patients who are recovering from such injuries. In this paper, we propose a classification scheme for identifying healthy individuals and patients. In the proposed scheme, a dataset is first constructed from DTI images, after which the constructed dataset undergoes feature selection and classification. The experiment results show that the proposed scheme aids in the diagnosis of SCIs.<p />  <p>Language: en</p>
LA  - en
SN  - 1748-670X
UR  - http://dx.doi.org/10.1155/2014/276589
ID  - ref1
ER  -