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Magnetic induction tomography (MIT) is a non-invasive medical imaging technique with promising applications such as brain imaging and cryosurgery monitoring. Despite its potential, the realisation of medical MIT application is challenging. The computational complexity of both the forward and inverse problems, and specific MIT hardware design are the major limitations for the development of MIT research in medical imaging. The MIT forward modeling and linear system equations for large scale matrices are computationally expensive. This paper presents the implementation of GPU (graphics processing unit) for both forward and inverse problems in MIT research. For a given MIT mesh geometry composed of 167,488 tetrahedral elements, the GPU accelerated Biot-Savart Law for solving the free space magnetic field and magnetic vector potential is proved to be over 200 times faster compared to the time consumption of a CPU (central processing unit). The linear system equation arising from the forward and inverse problem, can also be accelerated using GPU. Both simulations and experimental results are presented based on a new GPU implementation. Laboratory experimental results are shown for a phantom study representing potential cryosurgery monitoring using an MIT system.

MAGNETIC INDUCTION TOMOGRAPHY WITH HIGH PERFORMANCE GPU IMPLEMENTATION