Introducing: DeepHead, Wide-band Electromagnetic Imaging Paradigm
A. Al-Saffar, L. Guo, A. Abbosh

TL;DR
DeepHead introduces a novel electromagnetic imaging approach that leverages wide-band data and double compression to achieve high-resolution, stable brain dielectric mapping in microwave imaging, validated through simulations and human trials.
Contribution
It presents a fully data-driven, stable microwave brain imaging method that utilizes wide-band signals and double compression for improved resolution and robustness.
Findings
Achieves high-resolution dielectric mapping of the brain.
Demonstrates stability and robustness in both simulations and real-world tests.
Outperforms traditional methods in handling under-determinism.
Abstract
Electromagnetic medical imaging in the microwave regime is a hard problem notorious for 1) instability 2) under-determinism. This two-pronged problem is tackled with a two-pronged solution that uses double compression to maximally utilizing the cheap unlabelled data to a) provide a priori information required to ease under-determinism and b) reduce sensitivity of inference to the input. The result is a stable solver with a high resolution output. DeepHead is a fully data-driven implementation of the paradigm proposed in the context of microwave brain imaging. It infers the dielectric distribution of the brain at a desired single frequency while making use of an input that spreads over a wide band of frequencies. The performance of the model is evaluated with both simulations and human volunteers experiments. The inference made is juxtaposed with ground-truth dielectric distribution in…
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Taxonomy
TopicsMicrowave Imaging and Scattering Analysis · Geophysical Methods and Applications · Sparse and Compressive Sensing Techniques
