The magnetic properties of nuclei have significant applications in medical imaging. These applications are possible because the relaxation properties and the resonance frequency for a nucleus depend upon its environment. Factors such as the presence of chemical bonds, paramagnetic ions and the rate of flow of fluids influence the magnetic resonance (MR) signal. Therefore, different regions of a biological sample produce different MR signals for the given imaging parameters. While the reasons for these differences are often so complex that interpretation is difficult, their existence yields an intrinsic subject contrast between tissues. It is possible to capture several images by changing imaging conditions with different contrasting between the tissues. Independent component analysis (ICA) applied to images provides identification of tissues with the similar response in different imaging conditions. In order to identify tumor regions we have used correlation between symmetrical brain r...egions and image segmentation based on pixel brightness.
Keywords:
Resonance frequencies / Relaxation property / Paramagnetic ions / MR signals / Imaging conditions / His / Given imaging / Brain / Brain tumors / Brain regions / Bond strength (chemical) / Biological samples
Source:
SISY 2011 - 9th International Symposium on Intelligent Systems and Informatics, Proceedings, 2011, 433-435
TY - CONF
AU - Mihailović, J.
AU - Savić, A.
AU - Bogdanović Pristov, Jelena
AU - Radotić, Ksenija
PY - 2011
UR - http://rimsi.imsi.bg.ac.rs/handle/123456789/448
AB - The magnetic properties of nuclei have significant applications in medical imaging. These applications are possible because the relaxation properties and the resonance frequency for a nucleus depend upon its environment. Factors such as the presence of chemical bonds, paramagnetic ions and the rate of flow of fluids influence the magnetic resonance (MR) signal. Therefore, different regions of a biological sample produce different MR signals for the given imaging parameters. While the reasons for these differences are often so complex that interpretation is difficult, their existence yields an intrinsic subject contrast between tissues. It is possible to capture several images by changing imaging conditions with different contrasting between the tissues. Independent component analysis (ICA) applied to images provides identification of tissues with the similar response in different imaging conditions. In order to identify tumor regions we have used correlation between symmetrical brain regions and image segmentation based on pixel brightness.
C3 - SISY 2011 - 9th International Symposium on Intelligent Systems and Informatics, Proceedings
T1 - MRI brain tumors images by using independent component analysis
EP - 435
SP - 433
DO - 10.1109/SISY.2011.6034366
ER -
@conference{
author = "Mihailović, J. and Savić, A. and Bogdanović Pristov, Jelena and Radotić, Ksenija",
year = "2011",
abstract = "The magnetic properties of nuclei have significant applications in medical imaging. These applications are possible because the relaxation properties and the resonance frequency for a nucleus depend upon its environment. Factors such as the presence of chemical bonds, paramagnetic ions and the rate of flow of fluids influence the magnetic resonance (MR) signal. Therefore, different regions of a biological sample produce different MR signals for the given imaging parameters. While the reasons for these differences are often so complex that interpretation is difficult, their existence yields an intrinsic subject contrast between tissues. It is possible to capture several images by changing imaging conditions with different contrasting between the tissues. Independent component analysis (ICA) applied to images provides identification of tissues with the similar response in different imaging conditions. In order to identify tumor regions we have used correlation between symmetrical brain regions and image segmentation based on pixel brightness.",
journal = "SISY 2011 - 9th International Symposium on Intelligent Systems and Informatics, Proceedings",
title = "MRI brain tumors images by using independent component analysis",
pages = "435-433",
doi = "10.1109/SISY.2011.6034366"
}
Mihailović, J., Savić, A., Bogdanović Pristov, J.,& Radotić, K.. (2011). MRI brain tumors images by using independent component analysis. in SISY 2011 - 9th International Symposium on Intelligent Systems and Informatics, Proceedings, 433-435.
https://doi.org/10.1109/SISY.2011.6034366
Mihailović J, Savić A, Bogdanović Pristov J, Radotić K. MRI brain tumors images by using independent component analysis. in SISY 2011 - 9th International Symposium on Intelligent Systems and Informatics, Proceedings. 2011;:433-435.
doi:10.1109/SISY.2011.6034366 .
Mihailović, J., Savić, A., Bogdanović Pristov, Jelena, Radotić, Ksenija, "MRI brain tumors images by using independent component analysis" in SISY 2011 - 9th International Symposium on Intelligent Systems and Informatics, Proceedings (2011):433-435,
https://doi.org/10.1109/SISY.2011.6034366 . .
