Brain Mapping Using Neuroimaging
Author(s) -
WooSuk Tae,
ShinHyuk Kang,
ByungJoo Ham,
ByungJo Kim,
SungBom Pyun
Publication year - 2016
Publication title -
han-guk hyeonmigyeong hakoeji/applied microscopy
Language(s) - English
Resource type - Journals
eISSN - 2287-4445
pISSN - 2234-6198
DOI - 10.9729/am.2016.46.4.179
Subject(s) - neuroimaging , gyrification , diffusion mri , neuroscience , magnetic resonance imaging , functional magnetic resonance imaging , voxel , brain mapping , voxel based morphometry , brain morphometry , psychology , medicine , computer science , artificial intelligence , radiology , cerebral cortex , white matter
MRI has been widely used in hospitals for disease diagnosis, staging and follow-up, which has the advantage of avoiding needlessly the body to ionizing radiation. Magnetic resonance imaging (MRI) is playing a crucial role in the study of neuropsychiatric diseases, and the usefulness of MRI has been rapidly increased. MRI delineates the structural and functional alterations determined by disease conditions. Modern MRI technologies are of great interest due to MRI’s potential to characterize the signature of each neurodegenerative process and help both the diagnostic aspect and the monitoring of disease development (Agosta et al., 2016). Structural MRI has become the standard for routine clinical procedure; it shows anatomical detail with high sensitivity to pathology (Mak et al., 2016). Relatively new quantitative measures of diffusion tensor imaging (DTI) and fMRI are commonly used for research and clinical purposes and will soon become standard clinical tools (Christidi et al., 2016; Hu et al., 2016). Recently, DTI technique has advanced to the point that it has very high resolution with pathology specific details. It has revealed microstructural changes in the axon and myelin of brain white matter. Functional MRI (fMRI), on the other hand, measures brain activity indirectly; Task specific or disease related intrinsic network of brain area could be identifiable. In this review paper, we will introduce common MRI based neuroimaging modalities and analysis techniques. To understand the strengths and limitations of each neuroimaging analysis, the details of the imaging characteristics for each technique will be explained.
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