Electrical impedance tomography provides information of brain injury during total aortic arch replacement through its correlation with relative difference of neurological biomarkers.

Postoperative neurological dysfunction (PND) is one of the most common complications after a total aortic arch replacement (TAAR). Electrical impedance tomography (EIT) monitoring of cerebral hypoxia injury during TAAR is a promising technique for preventing the occurrence of PND. This study aimed to explore the feasibility of electrical impedance tomography (EIT) for warning of potential brain injury during total aortic arch replacement (TAAR) through building the correlation between EIT extracted parameters and variation of neurological biomarkers in serum. Patients with Stanford type A aortic dissection and requiring TAAR who were admitted between December 2021 to March 2022 were included. A 16-electrode EIT system was adopted to monitor each patient's cerebral impedance intraoperatively. Five parameters of EIT signals regarding to the hypothermic circulatory arrest (HCA) period were extracted. Meanwhile, concentration of four neurological biomarkers in serum were measured regarding to time before and right after surgery, 12 h, 24 h and 48 h after surgery. The correlation between EIT parameters and variation of serum biomarkers were analyzed. A total of 57 TAAR patients were recruited. The correlation between EIT parameters and variation of biomarkers were stronger for patients with postoperative neurological dysfunction (PND(+)) than those without postoperative neurological dysfunction (PND(-)) in general. Particularly, variation of S100B after surgery had significantly moderate correlation with two parameters regarding to the difference of impedance between left and right brain which were MRAIabs and TRAIabs (0.500 and 0.485 with p < 0.05, respectively). In addition, significantly strong correlations were seen between variation of S100B at 24 h and the difference of average resistivity value before and after HCA phase (ΔARVHCA), the slope of electrical impedance during HCA (kHCA) and MRAIabs (0.758, 0.758 and 0.743 with p < 0.05, respectively) for patients with abnormal S100B level before surgery. Strong correlations were seen between variation of TAU after surgery and ΔARVHCA, kHCA and the time integral of electrical impedance for half flow of perfusion (TARVHP) (0.770, 0.794 and 0.818 with p < 0.01, respectively) for patients with abnormal TAU level before surgery. Another two significantly moderate correlations were found between TRAIabs and variation of GFAP at 12 h and 24 h (0.521 and 0.521 with p < 0.05, respectively) for patients with a normal GFAP serum level before surgery. The correlations between EIT parameters and serum level of neurological biomarkers were significant in patients with PND, especially for MRAIabs and TRAIabs, indicating that EIT may become a powerful assistant for providing a real-time warning of brain injury during TAAR from physiological perspective and useful guidance for intensive care units.

A preliminary study on the application of electrical impedance tomography based on cerebral perfusion monitoring to intracranial pressure changes.

Background: In intracranial pathologic conditions of intracranial pressure (ICP) disturbance or hemodynamic instability, maintaining appropriate ICP may reduce the risk of ischemic brain injury. The change of ICP is often accompanied by the change of intracranial blood status. As a non-invasive functional imaging technique, the sensitivity of electrical impedance tomography (EIT) to cerebral hemodynamic changes has been preliminarily confirmed. However, no team has conducted a feasibility study on the dynamic detection of ICP by EIT technology from the perspective of non-invasive whole-brain blood perfusion monitoring. In this study, human brain EIT image sequence was obtained by in vivo measurement, from which a variety of indicators that can reflect the tidal changes of the whole brain impedance were extracted, in order to establish a new method for non-invasive monitoring of ICP changes from the level of cerebral blood perfusion monitoring. Methods: Valsalva maneuver (VM) was used to temporarily change the cerebral blood perfusion status of volunteers. The electrical impedance information of the brain during this process was continuously monitored by EIT device and real-time imaging was performed, and the hemodynamic indexes of bilateral middle cerebral arteries were monitored by transcranial Doppler (TCD). The changes in monitoring information obtained by the two techniques were compared and observed. Results: The EIT imaging results indicated that the image sequence showed obvious tidal changes with the heart beating. Perfusion indicators of vascular pulsation obtained from EIT images decreased significantly during the stabilization phase of the intervention (PAC: 242.94 ± 100.83, p < 0.01); perfusion index which reflects vascular resistance increased significantly in the stable stage of intervention (PDT: 79.72 ± 18.23, p < 0.001). After the intervention, the parameters gradually returned to the baseline level before compression. The changes of EIT indexes in the whole process are consistent with the changes of middle cerebral artery velocity related indexes shown in TCD results. Conclusion: The EIT image combined with the blood perfusion index proposed in this paper can reflect the decrease of cerebral blood flow under the condition of increased ICP in real time and intuitively. With the advantages of high time resolution and high sensitivity, EIT provides a new idea for non-invasive bedside measurement of ICP.

Multi-path Fusion in SFCF-Net for Enhanced Multi-frequency Electrical Impedance Tomography.

Multi-frequency electrical impedance tomography (mfEIT) offers a nondestructive imaging technology that reconstructs the distribution of electrical characteristics within a subject based on the impedance spectral differences among biological tissues. However, the technology faces challenges in imaging multi-class lesion targets when the conductivity of background tissues is frequency-dependent. To address these issues, we propose a spatial-frequency cross-fusion network (SFCF-Net) imaging algorithm, built on a multi-path fusion structure. This algorithm uses multi-path structures and hyper-dense connections to capture both spatial and frequency correlations between multi-frequency conductivity images, which achieves differential imaging for lesion targets of multiple categories through cross-fusion of information. According to both simulation and physical experiment results, the proposed SFCF-Net algorithm shows an excellent performance in terms of lesion imaging and category discrimination compared to the weighted frequency-difference, U-Net, and MMV-Net algorithms. The proposed algorithm enhances the ability of mfEIT to simultaneously obtain both structural and spectral information from the tissue being examined and improves the accuracy and reliability of mfEIT, opening new avenues for its application in clinical diagnostics and treatment monitoring.

Semi-Supervised Thyroid Nodule Detection in Ultrasound Videos.

Deep learning techniques have been investigated for the computer-aided diagnosis of thyroid nodules in ultrasound images. However, most existing thyroid nodule detection methods were simply based on static ultrasound images, which cannot well explore spatial and temporal information following the clinical examination process. In this paper, we propose a novel video-based semi-supervised framework for ultrasound thyroid nodule detection. Especially, considering clinical examinations that need to detect thyroid nodules at the ultrasonic probe positions, we first construct an adjacent frame guided detection backbone network by using adjacent supporting reference frames. To further reduce the labour-intensive thyroid nodule annotation in ultrasound videos, we extend the video-based detection in a semi-supervised manner by using both labeled and unlabeled videos. Based on the detection consistency in sequential neighbouring frames, a pseudo label adaptation strategy is proposed for the refinement of unpredicted frames. The proposed framework is validated on 996 transverse viewed and 1088 longitudinal viewed ultrasound videos. Experimental results demonstrated the superior performance of our proposed method in the ultrasound video-based detection of thyroid nodules.

Highly Robust and Strain-Resilient Thin Film Conductors Featuring Brittle Materials.

Stretchable conductors with stable electrical conductivity under various deformations are essential for wearable electronics, soft robots, and biointegrated devices. However, brittle film-based conductors on elastomeric substrates often suffer from unexpected electrical disconnection due to the obvious mechanical incompatibility between stiff films and soft substrates. We proposed a novel out-of-plane crack control strategy to achieve the strain-insensitive electrical performance of thin-film-based conductors, featuring conductive brittle materials, including nanocrystalline metals (Cu, Ag, Mo) and transparent oxides (ITO). Our metal film-based conductors exhibit an ultrahigh initial conductivity (1.3 × 105 S cm-1) and negligible resistance change (R/R0 = 1.5) over wide strain range from 0 to 130%, enabled by film-induced substrate cracking and liquid metal-induced electrical self-repairing. They could function well under multimodal deformations (stretching, bending, and twisting) and severe mechanical damage (cutting and puncturing). We demonstrated the strain-resilient electrical functionality of metal film-based conductors in a flexible light-emitting diode display that shows high mechanical compliance.

Observing the Clinical Outcomes of Single Port Endoscopic Posterolateral TLIF in Retired Athletes

Objective To investigate the clinical outcomes of single port endoscopic posterolateral transforaminal lumbar interbody fusion (TLIF) in athletic patients. Methods Retrospective analysis was done on the clinical information of 82 athletic patients suffering from degenerative scoliosis who were operated at our hospital's spine surgery department from April 2020 to December 2021. They were split into an observing and a controlling group using the random number table approach, with 41 cases per group. The controlling group had open TLIF therapy, whereas the observing group received single-hole endoscopic TLIF. Both groups' operational indicators were scrutinized. We contrasted the preoperative and postoperative results of both groups for the Visual Analog Scale (VAS), Oswestry Disability Index (ODI), Japanese Orthopedic Association score (JOA), Cobb angle, lumbar lordosis angle, sacral inclination angle, and Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36). Both groups' postoperative bone graft fusion was seen. Results Athletic Patients in the observing group underwent operations with considerably less time and blood loss versus to those in the controlling group (P <0.05). In terms of surgical drainage volume and hospital stay, there was no clinically meaningful variation among both groups (P > 0.05). The VAS and ODI scores of both groups were substantially lower after surgery than before, whereas the JOA score was substantially greater (P <0.05). After the procedure, the observing group's VAS and ODI scores were substantially lower versus to those of the controlling group, although their JOA scores were substantially higher (P <0.05). (AU)

Early detection of acute ischemic stroke using Contrast-enhanced electrical impedance tomography perfusion.

A cerebral contrast-enhanced electrical impedance tomography perfusion method is developed for acute ischemic stroke during intravenous thrombolytic therapy. Several clinical contrast agents with stable impedance characteristics and high-conductivity contrast were screened experimentally as electrical impedance contrast agent candidates. The electrical impedance tomography perfusion method was tested on rabbits with focal cerebral infarction, and its capability for early detection was verified based on perfusion images. The experimental results showed that ioversol 350 performed significantly better as an electrical impedance contrast agent than other contrast agents (p < 0.01). Additionally, perfusion images of focal cerebral infarction in rabbits confirmed that the electrical impedance tomography perfusion method could accurately detect the location and area of different cerebral infarction lesions (p < 0.001). Therefore, the cerebral contrast-enhanced electrical impedance tomography perfusion method proposed herein combines traditional, dynamic continuous imaging with rapid detection and could be applied as an early, rapid-detection, auxiliary, bedside imaging method for patients after a suspected ischemic stroke in both prehospital and in-hospital settings.

Effective Electrical Impedance Tomography Based on Enhanced Encoder-Decoder Using Atrous Spatial Pyramid Pooling Module.

Electrical impedance tomography (EIT) is a noninvasive and radiation-free imaging method. As a "soft-field" imaging technique, in EIT, the target signal in the center of the measured field is frequently swamped by the target signal at the edge, which restricts its further application. To alleviate this problem, this study presents an enhanced encoder-decoder (EED) method with an atrous spatial pyramid pooling (ASPP) module. The proposed method enhances the ability to detect central weak targets by constructing an ASPP module that integrates multiscale information in the encoder. The multilevel semantic features are fused in the decoder to improve the boundary reconstruction accuracy of the center target. The average absolute error of the imaging results by the EED method reduced by 82.0%, 83.6%, and 36.5% in simulation experiments and 83.0%, 83.2%, and 36.1% in physical experiments compared with the errors of the damped least-squares algorithm, Kalman filtering method, and U-Net-based imaging method, respectively. The average structural similarity improved by 37.3%, 42.9%, and 3.6%, and 39.2%, 45.2%, and 3.8% in the simulation and physical experiments, respectively. The proposed method provides a practical and reliable means of extending the application of EIT by solving the problem of weak central target reconstruction under the effect of strong edge targets in EIT.

Real-time imaging of traumatic brain injury using magnetic induction tomography.

Objective. Early diagnosis of traumatic brain injury (TBI) is crucial for its prognosis; however, traditional computed tomography diagnostic methods rely on large medical devices with an associated lag time to receive results. Therefore, an imaging modality is needed that provides real-time monitoring, can easily be carried out to assess the extent of TBI damage, and thus guides treatment.Approach. In the present study, an improved magnetic induction tomography (MIT) data acquisition system was used to monitor TBI in an animal model and distinguish the injury level. A pneumatically controlled cortical impactor was used to strike the parietal lobe of anesthetized rabbits two or three times under the same parameter mode to establish two different rabbit models of TBI. The MIT data acquisition system was used to record data and continuously monitor the brain for one hour without intervention.Main results. A target with increased conductivity was clearly observed in the reconstructed image. The position was relatively fixed and accurate, and the average positioning error of the image was 0.013 72 m. The normalized mean reconstruction value of all images increased with time. The slope of the regression line of the normalized mean reconstruction value differed significantly between the two models (p< 0.0001).Significance. This indicates that in the animal model, the unique features of MIT may facilitate the early monitoring of TBI and distinguish different degrees of injuries, thereby reducing the risk and mortality of associated complications.

Magnetic nanometer combined with microwave: Novel rapid thawing promotes phenolics release in frozen-storage lychee.

Magnetic nanometer combined with microwave thawing (MN-MT) could become a novel solution to challenges uneven and overheating of microwave thawing (MT), while retaining high thawing efficiency, compared to conventional water immersion thawing (WT). In this study, MN-MT was applied to thaw fruit (lychee as an example) for the first time, and was evaluated by comparison with WT, MT and water immersion combined with microwave thawing (WI-MT). Results showed that MN-MT could significantly shorten the thawing time of frozen lychee by 80.67%, 25.86% and 18.83% compared to WT, MT and WI-MT, respectively. Compared to WT, MN-MT was the only thawing treatment which significantly enhanced the release of quercetin-3-O-rutinose-7-O-α-l-rhamnoside, according to HPLC-DAD. Meanwhile, thermal-sensitive procyanidin B2, phenylpropionic acid and protocatechuic acid were found to be protected from degradations only by MN-MT based on UPLC-ESI-QTOF-MS/MS results. In summary, MN-MT is a potential novel treatment for rapid thawing and quality maintenance of frozen fruits.

Fast Iterative Shrinkage-Thresholding Algorithm with Continuation for Brain Injury Monitoring Imaging Based on Electrical Impedance Tomography.

Electrical impedance tomography (EIT) is low-cost and noninvasive and has the potential for real-time imaging and bedside monitoring of brain injury. However, brain injury monitoring by EIT imaging suffers from image noise (IN) and resolution problems, causing blurred reconstructions. To address these problems, a least absolute shrinkage and selection operator model is built, and a fast iterative shrinkage-thresholding algorithm with continuation (FISTA-C) is proposed. Results of numerical simulations and head phantom experiments indicate that FISTA-C reduces IN by 63.2%, 47.2%, and 29.9% and 54.4%, 44.7%, and 22.7%, respectively, when compared with the damped least-squares algorithm, the split Bergman, and the FISTA algorithms. When the signal-to-noise ratio of the measurements is 80-50 dB, FISTA-C can reduce IN by 83.3%, 72.3%, and 68.7% on average when compared with the three algorithms, respectively. Both simulation and phantom experiments suggest that FISTA-C produces the best image resolution and can identify the two closest targets. Moreover, FISTA-C is more practical for clinical application because it does not require excessive parameter adjustments. This technology can provide better reconstruction performance and significantly outperforms the traditional algorithms in terms of IN and resolution and is expected to offer a general algorithm for brain injury monitoring imaging via EIT.

A pilot study of contrast-enhanced electrical impedance tomography for real-time imaging of cerebral perfusion.

Background: Real-time detection of cerebral blood perfusion can prevent adverse reactions, such as cerebral infarction and neuronal apoptosis. Our previous clinical trial have shown that the infusion of therapeutic fluid can significantly change the impedance distribution in the brain. However, whether this alteration implicates the cerebral blood perfusion remains unclear. To explore the feasibility of monitoring cerebral blood perfusion, the present pilot study established a novel cerebral contrast-enhanced electrical impedance tomography (C-EIT) technique. Materials and methods: Rabbits were randomly divided into two groups: the internal carotid artery non-occlusion (ICAN) and internal carotid artery occlusion (ICAO) groups. Both of groups were injected with glucose, an electrical impedance-enhanced contrast agent, through the right internal carotid artery under EIT monitoring. The C-EIT reconstruction images of the rabbits brain were analyzed according to the collected raw data. The paired and independent t-tests were used to analyze the remodeled impedance values of the left and right cerebral hemispheres within and between studied groups, respectively. Moreover, pathological examinations of brain were performed immediately after C-EIT monitoring. Results: According to the reconstructed images, the impedance value of the left cerebral hemisphere in the ICAN group did not change significantly, whereas the impedance value of the right cerebral hemisphere gradually increased, reaching a peak at approximately 10 s followed by gradually decreased. In the ICAO group, the impedance values of both cerebral hemispheres increased gradually and then began to decrease after reaching the peak value. According to the paired t-test, there was a significant difference (P < 0.001) in the remodeling impedance values between the left and right hemispheres in the ICAN group, and there was also a significant difference (P < 0.001) in the ICAO group. According to the independent t-test, there was a significant difference (P < 0.001) of the left hemispheres between the ICAN and ICAO groups. Conclusion: The cerebral C-EIT proposed in this pilot study can reflect cerebral blood perfusion. This method has potential in various applications in the brain in the future, including disease progression monitoring, collateral circulation judgment, tumor-specific detection, and brain function research.

Temperature dependence of dielectric properties of blood at 10 Hz-100 MHz.

The temperature dependence of the dielectric properties of blood is important for studying the biological effects of electromagnetic fields, electromagnetic protection, disease diagnosis, and treatment. However, owing to the limitations of measurement methods, there are still some uncertainties regarding the temperature characteristics of the dielectric properties of blood at low and medium frequencies. In this study, we designed a composite impedance measurement box with high heat transfer efficiency that allowed for a four/two-electrode measurement method. Four-electrode measurements were carried out at 10 Hz-1 MHz to overcome the influence of electrode polarization, and two-electrode measurements were carried out at 100 Hz-100 MHz to avoid the influence of distribution parameters, and the data was integrated to achieve dielectric measurements at 10 Hz-100 MHz. At the same time, the temperature of fresh blood from rabbits was controlled at 17-39°C in combination with a temperature-controlled water sink. The results showed that the temperature coefficient for the real part of the resistivity of blood remained constant from 10 Hz to 100 kHz (-2.42%/°C) and then gradually decreased to -0.26%/°C. The temperature coefficient of the imaginary part was positive and bimodal from 6.31 kHz to 100 MHz, with peaks of 5.22%/°C and 4.14%/°C at 126 kHz and 39.8 MHz, respectively. Finally, a third-order function model was developed to describe the dielectric spectra at these temperatures, in which the resistivity parameter in each dispersion zone decreased linearly with temperature and each characteristic frequency increased linearly with temperature. The model could estimate the dielectric properties at any frequency and temperature in this range, and the maximum error was less than 1.39%, thus laying the foundation for subsequent studies.

Alteration in dough volume and gluten network of lychee pulp pomace bread base on mixture design dominated by particle size.

The reducing flavor of whole grain bread has been constantly affecting the consumption desire of a significant proportion of consumers. The study presents the use of lychee pulp pomace (LPP) powder to replace certain proportion of wheat flour and produce wheat bread with better quality, while having minimal effects on the volume and improving the nutritional quality. Distinct particle sizes (60-400 µm) of LPP powder were obtained by superfine or ordinary grinding. Effect of different additive proportions (7-19%) of LPP powder on bread dough quality were studied by constrained mixture designs. The volume of fermented doughs subsequently decreased after adding LPP powder. However, LPP powders with smaller particle sizes were able to minimize this effect due to its higher water-holding capacity. The analyses of gluten network showed that smaller particle sizes of LPP powder resulted in a decrease in surface hydrophobicity and increase in the elasticity and stability of gluten network. Finally, optimum mixture formula was composed of 16% LPP powder with 60 µm particle size and 15% water. The study illustrated the potential to make high-quality bread with small particle size of LPP powder. PRACTICAL APPLICATION: The addition of dietary fiber to wheat flour can adversely affect the dough volume and reduce the dough quality. By reducing the particle size of lychee pulp pomace powder, this adverse effect could be minimized while increasing the content of dietary fiber and bound phenolics in the dough. This provides data for the production of high-quality lychee dough bread.

Novel Catabolic Pathway of Quercetin-3-O-Rutinose-7-O-α-L-Rhamnoside by Lactobacillus plantarum GDMCC 1.140: The Direct Fission of C-Ring.

Lychee pulp phenolics (LPP) is mainly catabolized in the host colon, increasing the abundances of Bacteroides and Lactobacillus. Herein, five selected gut microbial strains (Bacteroides uniformis, B. thetaiotaomicron, Lactobacillus rhamnosus, L. plantarum, and L. acidophilus) were separately incubated with LPP to ascertain the specific strains participating in phenolic metabolism and the corresponding metabolites. The results indicated that B. uniformis, L. rhamnosus, and L. plantarum were involved in LPP utilization, contributing to 52.37, 28.33, and 45.11% of LPP degradation after 48 h fermentation, respectively. Unprecedentedly, the metabolic pathway of the major phenolic compound quercetin-3-O-rutinose-7-O-α-L-rhamnoside by L. plantarum, appeared to be the direct fission of C-ring at C2-O1 and C3-C4 bonds, which was proved from the occurrence of two substances with the deprotonated molecule [M-H]- ion at m/z 299 and 459, respectively. Meanwhile, it was fully confirmed that B. uniformis participated in the catabolism of isorhamnetin glycoside and procyanidin B2. In the B. uniformis culture, kaempferol was synthesized through dehydroxylation of quercetin which could be catabolized into alphitonin by L. rhamnosus. Furthermore, LPP metabolites exerted higher antioxidant activity than their precursors and gave clues to understand the interindividual differences for phenolic metabolism by gut microbiota.

Osteopontin in autoimmune disorders: current knowledge and future perspective.

Osteopontin (OPN) is a multifunctional cytokine and adhesion molecule, as well as an unusual regulator for both innate and adaptive immune responses. Several immune cells can produce OPN, including dendritic cells (DCs), macrophages, and T lymphocytes. OPN expression is reported to be increased in a wide range of disorders, including autoimmunity, cancer, and allergy. The overexpression of OPN in several autoimmune disorders, such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), multiple sclerosis (MS), Type 1 diabetes (T1D), inflammatory bowel disease (IBD), Sjögren's, and myasthenia gravis, have been shown to be correlated with disease severity. Regarding the important regulatory roles of OPN in the immune system, this study aimed to review the role of this molecule in autoimmune disorders and to provide a complete view of the current knowledge in this field.

miR-637 Inhibits Osteogenic Differentiation of Human Intervertebral Disc Cartilage Endplate Stem Cells by Targeting WNT5A.

Background: Degenerative disk disease (DDD) remains the leading incentive of severe lumbago. DDD is mainly caused by degeneration of cartilage endplate (CEP). Cartilage endplate stem cells (CESCs) are essential in chondrogenesis and osteogenesis of CEP. This study investigated the mechanism of miR-637 inhibiting osteogenic differentiation of human CESC by regulating WNT5A.Methods: The degenerative CEP (N = 10) and non-degenerative CEP (N = 6) were obtained from patients undergoing disk fusion surgery. CESCs were examined for surface stem cell markers, alkaline phosphatase (ALP) levels, osteogenic differentiation, osteogenic genes (Runx2, COL1), and chondrogenic gene (COL2). The miR-637 expression in CESCs was detected. The targeting relationship of miR-637 and WNT5A was confirmed. After miR-637 overexpression/WNT5A down-regulation, the action of miR-637/WNT5A on osteogenic differentiation of CESCs was evaluated. After simultaneous overexpression of miR-637/WNT5A, the effect of miR-637 on osteogenic differentiation of CESCs was assessed.Results: miR-637 was down-expressed in degenerative CESCs (D-CESCs), and miR-637 overexpression inhibited the osteogenic differentiation of D-CESCs, while inhibition of miR-637 promoted the osteogenic differentiation ability of D-CESCs. miR-637 targeted WNT5A and down-regulation of WNT5A inhibited the osteogenic differentiation of D-CESCs. Up-regulated WNT5A partially annulled the inhibitory action of miR-637 overexpression on osteogenic differentiation of D-CESCs.Conclusion: miR-637 inhibited osteogenic differentiation of D-CESCs via targeting WNT5A.

Removing Clinical Motion Artifacts During Ventilation Monitoring With Electrical Impedance Tomography: Introduction of Methodology and Validation With Simulation and Patient Data.

OBJECTIVE: Electrical impedance tomography (EIT) is a bedside tool for lung ventilation and perfusion assessment. However, the ability for long-term monitoring diminished due to interferences from clinical interventions and motion artifacts. The purpose of this study is to investigate the feasibility of the discrete wavelet transform (DWT) to detect and remove the common types of motion artifacts in thoracic EIT. METHODS: Baseline drifting, step-like and spike-like interferences were simulated to mimic three common types of motion artifacts. The discrete wavelet decomposition was employed to characterize those motion artifacts in different frequency levels with different wavelet coefficients, and those motion artifacts were then attenuated by suppressing the relevant wavelet coefficients. Further validation was conducted in two patients when motion artifacts were introduced through pulsating mattress and deliberate body movements. The db8 wavelet was used to decompose the contaminated signals into several sublevels. RESULTS: In the simulation study, it was shown that, after being processed by DWT, the signal consistency improved by 92.98% for baseline drifting, 97.83% for the step-like artifact, and 62.83% for the spike-like artifact; the signal similarity improved by 77.49% for baseline drifting, 73.47% for the step-like artifact, and 2.35% for the spike-like artifact. Results from patient data demonstrated the EIT image errors decreased by 89.24% (baseline drifting), 88.45% (step-like artifact), and 97.80% (spike-like artifact), respectively; the data correlations between EIT images without artifacts and the processed were all > 0.95. CONCLUSION: This study found that DWT is a universal and effective tool to detect and remove these motion artifacts.

A polarization-based image restoration method for both haze and underwater scattering environment.

Existing polarization-based defogging algorithms rely on the polarization degree or polarization angle and are not effective enough in scenes with little polarized light. In this article, a method of image restoration for both haze and underwater scattering environment is proposed. It bases on the general assumption that gray variance and average gradient of a clear image are larger than those of an image in a scattering medium. Firstly, based on the assumption, polarimetric images with the maximum variance (Ibest) and minimum variance (Iworst) are calculated from the captured four polarization images. Secondly, the transmittance is estimated and used to remove the scattering light from background medium of Ibest and Iworst. Thirdly, two images are fused to form a clear image and the color is also restored. Experimental results show that the proposed method obtains clear restored images both in haze and underwater scattering media. Because it does not rely on the polarization degree or polarization angle, it is more universal and suitable for scenes with little polarized light.

Advances of deep learning in electrical impedance tomography image reconstruction.

Electrical impedance tomography (EIT) has been widely used in biomedical research because of its advantages of real-time imaging and nature of being non-invasive and radiation-free. Additionally, it can reconstruct the distribution or changes in electrical properties in the sensing area. Recently, with the significant advancements in the use of deep learning in intelligent medical imaging, EIT image reconstruction based on deep learning has received considerable attention. This study introduces the basic principles of EIT and summarizes the application progress of deep learning in EIT image reconstruction with regards to three aspects: a single network reconstruction, deep learning combined with traditional algorithm reconstruction, and multiple network hybrid reconstruction. In future, optimizing the datasets may be the main challenge in applying deep learning for EIT image reconstruction. Adopting a better network structure, focusing on the joint reconstruction of EIT and traditional algorithms, and using multimodal deep learning-based EIT may be the solution to existing problems. In general, deep learning offers a fresh approach for improving the performance of EIT image reconstruction and could be the foundation for building an intelligent integrated EIT diagnostic system in the future.