Brain Injury Localization and Size Estimation Using Electromagnetic Symmetric Crossing Lines Method

Article

Zhu, Guohun, Bialkowski, Alina, Crozier, Stuart, Guo, Lei, Nguyen, Phong Thanh, Stancombe, Anthony E. and Abbosh, Amin. 2023. "Brain Injury Localization and Size Estimation Using Electromagnetic Symmetric Crossing Lines Method." IEEE Transactions on Instrumentation and Measurement. 72. https://doi.org/10.1109/TIM.2023.3295014

Article Title	Brain Injury Localization and Size Estimation Using Electromagnetic Symmetric Crossing Lines Method
ERA Journal ID	979
Article Category	Article
Authors	Zhu, Guohun, Bialkowski, Alina, Crozier, Stuart, Guo, Lei, Nguyen, Phong Thanh, Stancombe, Anthony E. and Abbosh, Amin
Journal Title	IEEE Transactions on Instrumentation and Measurement
Journal Citation	72
Year	2023
Publisher	IEEE (Institute of Electrical and Electronics Engineers)
Place of Publication	United States
ISSN	0018-9456
	1557-9662
Digital Object Identifier (DOI)	https://doi.org/10.1109/TIM.2023.3295014
Web Address (URL)	https://ieeexplore.ieee.org/document/10183777
Abstract	Based on the hypothesis that healthy human brains are highly symmetric along the sagittal plane, a method to detect and localize brain injuries using the intersection of pairs of signals captured by symmetrical antennas surrounding the head is presented. The method localizes the target using information at the low-frequency band, whereas the shape of the target is estimated using information from the high-frequency band. Then, an intersection of two pairs of antennas enables identifying the position of the target. Finally, a heat map is used to visualize the injury. The results indicate that crossing pairs of signals from the hemisphere with injury exhibit significantly different amplitudes in the graph features compared to those not crossing the target ( $p < 0.003$ ). The experiments show that the proposed localization algorithm can achieve an accuracy of 0.85 ± 0.08 Dice similarity coefficient based on 150 experimental measurements on head phantoms.
Keywords	Brain injury; complex networks; differential strengths; electromagnetic imaging (EMI); symmetrical crossing lines
ANZSRC Field of Research 2020	4699. Other information and computing sciences
Public Notes	Files associated with this item cannot be displayed due to copyright restrictions.
Byline Affiliations	School of Mathematics, Physics and Computing
	University of Queensland

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