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Microwave Imaging Provides Brain Stroke Monitoring, Detection

Microwave tomography was used for monitoring the condition of a human brain.

Microwave tomography is widely used in medicine to create images of internal organs at work. One of the largest and most critical organs, of course, is the brain, and researchers at the Pierre and Marie Curie University, Centre Nationale de la Recherche Scientifique, France and the Jean-Alexandre Dieudonne Laboratory at the Universite Cote d’Azur, France have focused on the use of tomographic microwave imaging to detect and monitor the brain and use microwave tomography for monitoring the health of a typical human brain.

Their efforts brought about the development of a portable and transportable system that uses wireless microwave communications to transfer imaged data from the brain to a nearby computer for processing. The basis for monitoring the brain lies in the idea that a disturbance or stroke in the brain will result in a change in the complex permittivity that can be measured and monitored by a high-performance-computing (HPC) machine. The tomographic system was developed so that data could be collected from a patient’s brain, processed by the HPC, and then transferred wirelessly to a hospital. The solution requires advanced numerical modeling and high-speed parallel computing.

The system leverages the differences in the complex permittivity of diseased brain tissues in comparison to healthy brain tissues to perform detection. Measurements must be made with low-level microwave radiation and sensitive receivers, to avoid subjecting healthy brain tissue to any unnecessary electromagnetic (EM) radiation. Using higher-order approximations, the researchers are able to achieve a high level of accuracy in their dielectric measurements in a relatively short computing time for the HPC machines. By working with a 10% noise level, the researchers were also capable of showing that the system proposal could be feasible for use under actual operating conditions (and noise).

See “Numerical Modeling and High-Speed Parallel Computing,” IEEE Antennas & Propagation Magazine, Vol. 59, No. 5, October 2017, p. 98.

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