Tay Bunheang, Hyun Jung Keun, Oh Sejong
Department of Nanobiomedical Science, Dankook University, Cheonan 330-714, Republic of Korea.
Comput Math Methods Med. 2014;2014:276589. doi: 10.1155/2014/276589. Epub 2014 Jan 21.
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.
扩散张量成像（DTI）使用体内图像，通过测量水分子的扩散来描述细胞外结构。这些图像利用回波平面成像捕捉轴突的运动和方向，并为评估中枢神经系统的损伤和结构损伤提供关键信息。该信息可用于预测脊髓损伤（SCI）以及评估正在从此类损伤中恢复的患者。在本文中，我们提出了一种用于识别健康个体和患者的分类方案。在所提出的方案中，首先从DTI图像构建一个数据集，然后对构建好的数据集进行特征选择和分类。实验结果表明，所提出的方案有助于脊髓损伤的诊断。
