ArticleSensors (Basel, Switzerland)2022
Three-Dimensional Microwave Head Imaging with GPU-Based FDTD and the DBIM Method.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Impact of Increasing Antenna Model Complexity on Microwave Tomography Using DBIM.Sensors (Basel, Switzerland) · 2026Article
- Subspace-Based Two-Step Iterative Shrinkage/Thresholding Algorithm for Microwave Tomography Breast Imaging.Sensors (Basel, Switzerland) · 2025Article
- Review of microwave imaging algorithms for stroke detection.Medical & biological engineering & computing · 2023Review
- A Novel Discretization Procedure in the CSI-FEM Algorithm for Brain Stroke Microwave Imaging.Sensors (Basel, Switzerland) · 2022Article
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Authors and funding
2 authors.
Funding
Abstract
We present a preliminary study of microwave head imaging using a three-dimensional (3-D) implementation of the distorted Born iterative method (DBIM). Our aim is to examine the benefits of using the more computationally intensive 3-D implementation in scenarios where limited prior information is available, or when the target occupies an area that is not covered by the imaging array's transverse planes. We show that, in some cases, the 3-D implementation outperforms its two-dimensional (2-D) counterpart despite the increased number of unknowns for the linear problem at each DBIM iteration. We also discuss how the 3-D algorithm can be implemented efficiently using graphic processing units (GPUs) and validate this implementation with experimental data from a simplified brain phantom. In this work, we have implemented a non-linear microwave imaging approach using DBIM with GPU-accelerated FDTD. Moreover, the paper offers a direct comparison of 2-D and 3-D microwave tomography implementations for head imaging and stroke detection in inhomogenous anatomically complex numerical head phantoms.
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