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1. High accurate and efficient electrical impedance tomography for fast brain imaging

   https://doi.org/10.1117/12.2659172  

   Tran, Hoang Van; Kim, Min Hyuck; Le, Thong Chi; Yoon, Hargsoon (January 2023, Nano-, Bio-, Info-Tech Sensors, and Wearable Systems 2023)

   Kim, Jaehwan; Oh, Ilkwon; Yoon, Hargsoon; Porfiri, Maurizio (Ed.)

   Electrical Impedance Tomography (EIT) is a medical imaging technique that reconstructs impedance distribution inside a target object by injecting electrical currents into pairs of electrodes and measuring induced voltages on the remaining electrodes. Since neural signals result from the activity of ion channels causing impedance changes in the cell membrane, EIT can image these neural activities for understanding brain function and medical purposes. In our research, our self-developed electronic prototype board was used to generate high-quality electrical current and collect the data on electrodes with a high sampling rate and bit-resolution. In image reconstruction, a preprocessing data analysis algorithm was newly developed and applied to improve the accuracy of our EIT imaging. The human head has complex anatomical geometry and non-uniform resistivity distribution along with the highly resistive skull, which makes brain-EIT remains challenging inaccurate image reconstruction. To mimic the human head, a multi-layered human head phantom was designed and tested to investigate the effect of the skull structure on imaging. In this presentation, comparison studies for measurements and simulation results will be introduced to discuss the source of errors and improve the accuracy and efficiency of our brain-EIT system. 

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2. A Krylov subspace type method for Electrical Impedance Tomography

   https://doi.org/10.1051/m2an/2021057  

   Pasha, Mirjeta; Kupis, Shyla; Ahmad, Sanwar; Khan, Taufiquar (November 2021, ESAIM: Mathematical Modelling and Numerical Analysis)

   Electrical Impedance Tomography (EIT) is a well-known imaging technique for detecting the electrical properties of an object in order to detect anomalies, such as conductive or resistive targets. More specifically, EIT has many applications in medical imaging for the detection and location of bodily tumors since it is an affordable and non-invasive method, which aims to recover the internal conductivity of a body using voltage measurements resulting from applying low frequency current at electrodes placed at its surface. Mathematically, the reconstruction of the internal conductivity is a severely ill-posed inverse problem and yields a poor quality image reconstruction. To remedy this difficulty, at least in part, we regularize and solve the nonlinear minimization problem by the aid of a Krylov subspace-type method for the linear sub problem during each iteration. In EIT, a tumor or general anomaly can be modeled as a piecewise constant perturbation of a smooth background, hence, we solve the regularized problem on a subspace of relatively small dimension by the Flexible Golub-Kahan process that provides solutions that have sparse representation. For comparison, we use a well-known modified Gauss–Newton algorithm as a benchmark. Using simulations, we demonstrate the effectiveness of the proposed method. The obtained reconstructions indicate that the Krylov subspace method is better adapted to solve the ill-posed EIT problem and results in higher resolution images and faster convergence compared to reconstructions using the modified Gauss–Newton algorithm. 

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3. Super-resolution reconstruction in ultrahigh-field MRI

   https://doi.org/10.1016/j.bpr.2023.100107  

   Payne, Macy; Mali, Ivina; Mueller, Thomas; Cain, Mary; Segev, Ronen; Bossmann, Stefan H. (June 2023, Biophysical Reports)

   Magnetic resonance imaging (MRI) is a highly significant imaging platform for a variety of medical and research applications. However, the low spatiotemporal resolution of conventional MRI limits its applicability toward rapid acquisition of ultrahigh-resolution scans. Current aims at high-resolution MRI focus on increasing the accuracy of tissue delineation, as- sessments of structural integrity, and early identification of malignancies. Unfortunately, high-resolution imaging often leads to decreased signal/noise (SNR) and contrast/noise (CNR) ratios and increased time cost, which are unfeasible in many clinical and academic settings, offsetting any potential benefits. In this study, we apply and assess the efficacy of super-res- olution reconstruction (SRR) through iterative back-projection utilizing through-plane voxel offsets. SRR allows for high-res- olution imaging in condensed time frames. Rat skulls and archerfish samples, typical models in academic settings, were used to demonstrate the impact of SRR on varying sample sizes and applicability for translational and comparative neuroscience. The SNR and CNR increased in samples that did not fully occupy the imaging probe and in instances where the low-resolution data were acquired in three dimensions, while the CNR was found to increase with both 3D and 2D low-resolution data recon- structions when compared with directly acquired high-resolution images. Limitations to the applied SRR algorithm were inves- tigated to determine the maximum ratios between low-resolution inputs and high-resolution reconstructions and the overall cost effectivity of the strategy. Overall, the study revealed that SRR could be used to decrease image acquisition time, in- crease the CNR in nearly all instances, and increase the SNR in small samples. 

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4. High-throughput single pixel spectral imaging system for glow discharge optical emission spectrometry elemental mapping enabled by compressed sensing

   https://doi.org/10.1039/D2JA00021K  

   Gamez, Gerardo; She, Yue; Rivera, Paola; Shi, Songyue; Finch, Kevin (February 2022, Journal of Analytical Atomic Spectrometry)

   Glow discharge optical emission spectroscopy elemental mapping (GDOES EM), enabled by spectral imaging strategies, is an advantageous technique for direct multi-elemental analysis of solid samples in rapid timeframes. Here, a single-pixel, or point scan, spectral imaging system based on compressed sensing image sampling, is developed and optimized in terms of matrix density, compression factor, sparsifying basis, and reconstruction algorithm for coupling with GDOES EM. It is shown that a 512 matrix density at a compression factor of 30% provides the highest spatial fidelity in terms of the peak signal-to-noise ratio (PSNR) and complex wavelet structural similarity index measure (cw-SSIM) while maintaining fast measurement times. The background equivalent concentration (BEC) of Cu I at 510.5 nm is improved when implementing the discrete wavelet transform (DWT) sparsifying basis and Two-step Iterative Shrinking/Thresholding Algorithm for Linear Inverse Problems (TwIST) reconstruction algorithm. Utilizing these optimum conditions, a GDOES EM of a flexible, etched-copper circuit board was then successfully demonstrated with the compressed sensing single-pixel spectral imaging system (CSSPIS). The newly developed CSSPIS allows taking advantage of the significant cost-efficiency of point-scanning approaches (>10× vs. intensified array detector systems), while overcoming (up to several orders of magnitude) their inherent and substantial throughput limitations. Ultimately, it has the potential to be implemented on readily available commercial GDOES instruments by adapting the collection optics. 

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5. Phase- shifted 3D Imaging of Rotating Milling/Drilling tools

   Guo, Xiangyu; Lee, ChaBum (October 2020, American Society for Precision Engineering)

   null (Ed.)

   Drilling and milling operations are material removal processes involved in everyday conventional productions, especially in the high-speed metal cutting industry. The monitoring of tool information (wear, dynamic behavior, deformation, etc.) is essential to guarantee the success of product fabrication. Many methods have been applied to monitor the cutting tools from the information of cutting force, spindle motor current, vibration, as well as sound acoustic emission. However, those methods are indirect and sensitive to environmental noises. Here, the in-process imaging technique that can capture the cutting tool information while cutting the metal was studied. As machinists judge whether a tool is worn-out by the naked eye, utilizing the vision system can directly present the performance of the machine tools. We proposed a phase shifted strobo-stereoscopic method (Figure 1) for three-dimensional (3D) imaging. The stroboscopic instrument is usually applied for the measurement of fast-moving objects. The operation principle is as follows: when synchronizing the frequency of the light source illumination and the motion of object, the object appears to be stationary. The motion frequency of the target is transferring from the count information of the encoder signals from the working rotary spindle. If small differences are added to the frequency, the object appears to be slowly moving or rotating. This effect can be working as the source for the phase-shifting; with this phase information, the target can be whole-view 3D reconstructed by 360 degrees. The stereoscopic technique is embedded with two CCD cameras capturing images that are located bilateral symmetrically in regard to the target. The 3D scene is reconstructed by the location information of the same object points from both the left and right images. In the proposed system, an air spindle was used to secure the motion accuracy and drilling/milling speed. As shown in Figure 2, two CCDs with 10X objective lenses were installed on a linear rail with rotary stages to capture the machine tool bit raw picture for further 3D reconstruction. The overall measurement process was summarized in the flow chart (Figure 3). As the count number of encoder signals is related to the rotary speed, the input speed (unit of RPM) was set as the reference signal to control the frequency (f0) of the illumination of the LED. When the frequency was matched with the reference signal, both CCDs started to gather the pictures. With the mismatched frequency (Δf) information, a sequence of images was gathered under the phase-shifted process for a whole-view 3D reconstruction. The study in this paper was based on a 3/8’’ drilling tool performance monitoring. This paper presents the principle of the phase-shifted strobe-stereoscopic 3D imaging process. A hardware set-up is introduced, , as well as the 3D imaging algorithm. The reconstructed image analysis under different working speeds is discussed, the reconstruction resolution included. The uncertainty of the imaging process and the built-up system are also analyzed. As the input signal is the working speed, no other information from other sources is required. This proposed method can be applied as an on-machine or even in-process metrology. With the direct method of the 3D imaging machine vision system, it can directly offer the machine tool surface and fatigue information. This presented method can supplement the blank for determining the performance status of the machine tools, which further guarantees the fabrication process. 

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