Three-Dimensional Microwave Head Imaging with GPU-Based FDTD and the DBIM Method

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.

A Novel Discretization Procedure in the CSI-FEM Algorithm for Brain Stroke Microwave Imaging

“…Some recent works on brain microwave imaging through quantitative reconstruction are [ 10 , 11 ], where the distorted Born iterative algorithm is used for the reconstruction of the head dielectric properties. Our results are comparable with those, especially for the focusing and positioning of the reconstructed target.…”

“…In addition, the CSI performances can be optimized through a regularization procedure, as in [ 27 ]. Moreover, the algorithm implementation can be sped up via programmable system-on-chip solutions [ 36 ] or via graphic processing units [ 11 ]. Finally, we plan to apply the implemented FEM-CSI algorithm to experimental data obtained through the system described in [ 20 ], applying a proper calibration technique, such as the one described in [ 37 ], to mitigate the discrepancy between the simulated and real antennas due to manufacturing tolerances.…”

“…The CSI method is an iterative nonlinear algorithm widely exploited in MWI technology, thanks to its capability to reconstruct the dielectric properties distribution quantitatively inside the DoI. Another quantitative algorithm used in the literature for brain microwave imaging is the distorted Born iterative method, as in [ 10 , 11 ].…”

Accelerated Medical Microwave Tomography via Heterogeneous Computing

“…MWT techniques are currently pursued in medical imaging applications which can benefit from relatively low-cost and portable technology [2], [3], [4]. While MWT experimental prototypes have been growing over the last two decades [5], [6], [7], [8], [9], [10], very few [2], [11], [12] are using three-dimensional (3D) MWT algorithms to fully exploit the EM wave signals captured by their respective antenna arrays.…”

“…Although semi-analytical techniques are possible [2], [13], developing purely computational approaches can accelerate the procedure without sacrificing accuracy. These include distributing the computation to multi-core architectures [11], [14] or (and) mapping part of the workload to graphics processing units (GPUs) [12], [15], [16].…”