A novel super-resolution volumetric photoacoustic microscopy, based on the theory of structured-illumination, is proposed in this paper. The structured-illumination will be introduced in order to surpass the diffraction limit in a photoacoustic microscopy (PAM) structure. Through optical excitation of the targeted object with a sinusoidal spatial fringe pattern, the object's frequency spectrum is forced to shift in the spatial frequency domain. The shifting in the desired direction leads to the passage of the high-frequency contents of the object through the passband of the acoustic diffraction frequency response. Finally, combining the low-frequency image with the high-frequency parts in four regular orientations in the spatial frequency domain is equivalent to imaging the targeted object with an imaging system of two-fold bandwidth and thus half lateral resolution. In order to obtain the image of out-of-focus regions and improve the lateral resolution outside the focal region of a PAM imaging system, Fourier-domain reconstruction algorithm based on the synthetic aperture focusing technique (SAFT) using the virtual detector concept is utilized for reduction in the required computational load and time. The performance of the proposed imaging system is validated with in vivo and ex vivo targets. The experimental results obtained from several tungsten filaments in the depth range of 1.2 mm, show an improvement of -6 dB lateral resolution from 55- [Formula: see text] to 25- [Formula: see text] and also an improvement of signal-to-noise ratio (SNR) from 16-22 dB to 27-33 dB in the proposed system.

This paper focuses on an ef?cient approach of designing multi-static arrays for millimeter-wave imaging, based on the k-space or Fourier-spatial domain characteristic of imaging systems. Our goal is to decrease the redundancy of the data measured by each antenna, and to improve the resolution of the reconstructed image. The proposed technique is based on determining the role of each transmitter and receiver, in collecting the data from each voxel of the target in k-space domain and then rotating transmitters' beams to measure the desirable information. The effect of non-uniform redundant k-space domain frequency samples that act as an undesirable ?lter, is compensated using a modi?ed SAR back-projection algorithm. Experimental and simulation results are presented and compared with that of a sparse multi-static array with the same number of transmitters and receivers. Our simulations and measurements show signi?cant improvement in terms of overall quality and edge preservation in the reconstructed images. Also, the obtained results demonstrate that using the proposed structure and algorithm, the average improvement in peak-signalto-noise ratio (PSNR), structural similarity index measure (SSIM) and digital image correlation (DIC) metrics of 3.03 dB, 0.22 and 0.173, are achieved, respectively.

In this paper, a new approach toward material detection and classification, based on the spectral analysis of millimeter-wave images, using machine learning technique is proposed. The focus of this paper is to detect concealed dangerous materials. It is shown that by using adequate number of training data captured from different materials of interest, the trained machine could detect concealed dangerous materials with an acceptable accuracy. The training phase is performed with materials of varying thickness, shape, background, covering layers and distance. The training data is collected with laboratory experiments in the frequency range of 27-31 GHz with 51 frequency samples. The results show more than 92 percent accuracy in differentiating various materials based on the true-alarm-rate (TAR) metric.

In this study, a thorough analysis of image reconstruction in an active millimetre‐wave (MMW) cylindrical imaging system is performed. To improve the system's performance in terms of the total cost as well as the coupling effect, sparse multi‐static arrays are desired. Nevertheless, the existing reconstruction methods fail to operate in sparse multi‐static antenna‐array systems. Therefore, to address these shortcomings, in this study, at first, the existing MMW mono‐static cylindrical image reconstruction methods are modified in both single‐frequency and wideband reconstruction platforms. Moreover, in order to further improve the image quality and the system cost, a sparse multi‐static one‐dimensional antenna array has been proposed. To use this sparse array in the cylindrical MMW imaging system, a novel multi‐static cylindrical image reconstruction method is also proposed. The performances of the proposed reconstruction methods for both mono‐static and sparse multi‐static cylindrical imaging structures are validated through numerical simulations. Through the obtained results, 83% reduction in antenna array cost along with a 25 dB decrease in coupling effect is achieved at the cost of a minor reduction in the reconstructed image quality.