As a rapidly developing novel electromagnetic imaging technique, microwave-induced thermoacoustic tomography (MITAT) has found many applications and attracted tremendous research interest. Using sparse data to reconstruct images is very challenging for MITAT. This work proposes a novel deep-learning-enabled MITAT (DL-MITAT) modality to address the sparse data reconstruction problem and applies it in breast cancer detection. The applied network is a domain transform network called feature projection network (FPNet) + ResU-Net. Detailed structure and implementation method of the network is described. We conduct both simulation and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ex vivo experiments with breast phantoms to test the validity of the DL-MITAT approach. The obtained images given by the trained network exhibit much better quality and have much less artifacts than those obtained by a traditional imaging algorithm. We show that only 15 measurements can still reliably recover an image of the breast tumor for both full-view and limited-view configurations in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ex vivo experiments. We also provide detailed discussions on the capability and limitations of the proposed scheme. This work presents a new paradigm for MITAT based on sparse data and can be applied in all related applications of MITAT, including biomedical imaging, nondestructive testing, and therapy guidance.

Deep-Learning-Enabled Microwave-Induced Thermoacoustic Tomography Based on Sparse Data for Breast Cancer Detection

Microwave-induced thermoacoustic tomography (MITAT) is suitable for detecting foreign bodies (FBs) in human body due to the sufficient microwave contrast between the FBs and surrounding human tissues. But detection of both hot and cold FBs by the same modality has not been demonstrated. In addition, traditional widely used imaging algorithms for MITAT requires highly intensive measurements, which is not cost-effective or time-efficient. This work reports the application of a low-cost compressive thermoacoustic tomography (CTAT) system for the detection of both hot and cold FBs embedded in tissues, referred to as FBD. We give detailed description of the theory of MITAT and CTAT. We show experimental demonstrations using different shaped metallic samples as the hot FBs and glass and wood samples as the cold FBs. We achieve successful detection of all the hot and cold FBs embedded in different tissues. The CTAT-FBD method is a new paradigm promising for a bunch of diagnosis or sensing applications. It is also possible to build a portable system for this technique.

A Low-Cost Compressive Thermoacoustic Tomography System for Hot and Cold Foreign Bodies Detection

Microwave-induced thermoacoustic imaging (MTAI) has emerged as a potential biomedical imaging modality with over 20-year growth. MTAI typically employs pulsed microwave as the pumping source, and detects the microwave-induced ultrasound wave via acoustic transducers. Therefore, it features high acoustic resolution, rich electromagnetic contrast, and large imaging depth. Benefiting from these unique advantages, MTAI has been extensively applied to various fields including pathology, biology, material and medicine. Till now, MTAI has been deployed for a wide range of biomedical applications, including cancer diagnosis, joint evaluation, brain investigation and endoscopy. This paper provides a comprehensive review on (1) essential physics (endogenous/exogenous contrast mechanisms, penetration depth and resolution), (2) hardware configurations and software implementations (excitation source, antenna, ultrasound detector and image recovery algorithm), (3) animal studies and clinical applications, and (4) future directions. 

Biomedical microwave-induced thermoacoustic imaging

There is a great need in temperature monitoring in biomedical applications. The current available temperature measurement techniques have some deficiencies in noninvasiveness, applicability, sensitivity and resolution. Microwave-induced thermoacoustic tomography (MITAT) has found diversified applications in biomedical related disciplines. It has been shown that MITAT can be used to estimate the temperature in a noninvasive manner. However, the applicability of the technique is still limited. This work presents experimental demonstration of two-dimensional (2-D) temperature detection of biological samples based on compressive TAT, referred to as MICTAT. Detailed principle of the method is established. A phantom sample and a biological sample are tested by experiments and 2-D temperature maps are obtained. This work provides a new route of getting 2-D temperature maps of biological samples and may find many applications in biomedical related areas.

2-D Noninvasive Temperature Measurement of Biological Samples Based on Compressive Thermoacoustic Tomography

Solving inverse scattering problems (ISPs) is challenging because of its intrinsic ill-posedness and the nonlinearity. When dealing with highly nonlinear ISPs, i.e., those scatterers with high contrast and/or electrically large size, the traditional iterative nonlinear inversion methods converge slowly and take lots of computation time, even maybe trapped into local wrong solution. To alleviate the above challenges, a learning-assisted (LA) inversion approach termed as the LA inversion method (LAIM) with advanced generative adversarial network (GAN) in virtue of a new recently established contraction integral equation for inversion (CIE-I) is proposed to achieve a good balance between the computational efficiency and the accuracy of solving highly nonlinear ISPs. The preliminary profiles composed of only small amount of low-frequency components can be got efficiently by the Fourier bases expansion of CIE-I inversion (FBE-CIE-I). The physically exacted information can be taken as the input of the neural network to recover super-resolution image with more high-frequency components. A weighted loss function composed of the adversarial loss, mean absolute percentage error (MAPE), and structural similarity (SSIM) is used under the pix2pix GAN framework. In addition, the self-attention module is used at the end of the generator network to capture the physical distance information between two pixels and enhance the inversion accuracy of the feature scatterers. To further improve the inversion efficiency, the data-driven method (DDM) is used to achieve real-time imaging by cascading U-net and pix2pix GAN, where U-net is used to replace FBE-CIE-I in the LAIM. Compared with other LA inversion, both the synthetic and experimental examples have validated the merits of the proposed LAIM and DDM. 

Learning-Assisted Inversion for Solving Nonlinear Inverse Scattering Problem

Objective: As a newly developed technique, focused microwave breast hyperthermia (FMBH) can provide accurate and cost-effective treatment of breast tumors with low side effect. A clinically feasible FMBH system requires a guidance technique to monitor the microwave power distribution in the breast. Compressive thermoacoustic tomography (CTT) is a suitable guidance approach for FMBH, which is more cost-effective than MRI. However, no experimental validation based on a realized FMBH-CTT system has been reported, which greatly hinders the further advancement of this novel approach. Methods: We developed a preclinical system prototype for the FMBH-CTT technique, containing a microwave phased antenna array, a microwave source, an ultrasound transducer array and associated data acquisition module. Results: Experimental results employing homogeneous and inhomogeneous breast-mimicking phantoms demonstrate that the CTT technique can offer reliable guidance for the entire process of the FMBH. In addition, small phase noises do not deteriorate the overall performance of the system prototype. Conclusion: The realized preclinical FMBH-CTT system prototype is capable for noninvasive, accurate and low-side-effect breast tumor treatment with effective guidance. Significance: The experimentally validated FMBH-CTT system prototype provides a feasible paradigm for CTT guided FMBH, establishes a practical platform for future improvement of this technique, and paves the way for potential clinical translation.

A Preclinical System Prototype for Focused Microwave Breast Hyperthermia Guided by Compressive Thermoacoustic Tomography

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A Preclinical System Prototype for Focused Microwave Breast Hyperthermia Guided by Compressive Thermoacoustic Tomography