Application of Self-Organizing Artificial Neural Networks on Simulated Diffusion Tensor Images
Joint Authors
Özkan, Mehmed
Göksel Duru, Dilek
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-05-12
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Diffusion tensor magnetic resonance imaging (DTMRI) as a noninvasive modality providing in vivo anatomical information allows determination of fiber connections which leads to brain mapping.
The success of DTMRI is very much algorithm dependent, and its verification is of great importance due to limited availability of a gold standard in the literature.
In this study, unsupervised artificial neural network class, namely, self-organizing maps, is employed to discover the underlying fiber tracts.
A common artificial diffusion tensor resource, named “phantom images for simulating tractography errors” (PISTE), is used for the accuracy verification and acceptability of the proposed approach.
Four different tract geometries with varying SNRs and fractional anisotropy are investigated.
The proposed method, SOFMAT, is able to define the predetermined fiber paths successfully with a standard deviation of (0.8–1.9) × 10−3 depending on the trajectory and the SNR value selected.
The results illustrate the capability of SOFMAT to reconstruct complex fiber tract configurations.
The ability of SOFMAT to detect fiber paths in low anisotropy regions, which physiologically may correspond to either grey matter or pathology (abnormality) and uncertainty areas in real data, is an advantage of the method for future studies.
American Psychological Association (APA)
Göksel Duru, Dilek& Özkan, Mehmed. 2013. Application of Self-Organizing Artificial Neural Networks on Simulated Diffusion Tensor Images. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-1010353
Modern Language Association (MLA)
Göksel Duru, Dilek& Özkan, Mehmed. Application of Self-Organizing Artificial Neural Networks on Simulated Diffusion Tensor Images. Mathematical Problems in Engineering No. 2013 (2013), pp.1-13.
https://search.emarefa.net/detail/BIM-1010353
American Medical Association (AMA)
Göksel Duru, Dilek& Özkan, Mehmed. Application of Self-Organizing Artificial Neural Networks on Simulated Diffusion Tensor Images. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-1010353
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1010353