Common Artifacts and Remedies in Histological Preparations

The importance of the accuracy of preparing biological specimen as histological sections that can be examined under a microscope lies in reflecting a true image of the tissue that includes all its components, which are used in scientific research or for the purpose of diagnosing various diseases of the body. Despite this, some cellular structures within the tissue may suffer from some alterations that result from the appearance of defects during any stage of preparing these microscopic sections, which alter or interfere with the precise cellular structures and morphology that constitute the tissue and thus give a different image for tissue features and cause confusion in the work histopathologist in the diagnosis. There are several reasons that can cause a misdiagnosis of the sample that occurs during the surgical separation process or after separation during the stages of microscopic preparation techniques from fixation stage, tissue processing, embedding or microtomy, staining until mounting procedures. The constant need to identify these defects and their causes in addition to try to reduce them is one of the biggest challenges evident in pathology laboratories. Therefore, this study aims to review the most common defects that occur in any stage of tissue processing, with an explanation of their causes and appropriate ways to avoid them.

Deep learning-based inpainting of saturation artifacts in optical coherence tomography images

Limited by the dynamic range of the detector,saturation artifacts usually occur in optical coherence tomography(OCT)imaging for high scattering media.The available methods are difficult to remove saturation artifacts and restore texture completely in OCT images.We proposed a deep learning-based inpainting method of saturation artifacts in this paper.The generation mechanism of saturation artifacts was analyzed,and experimental and simulated datasets were built based on the mechanism.Enhanced super-resolution generative adversarial networks were trained by the clear–saturated phantom image pairs.The perfect reconstructed results of experimental zebrafish and thyroid OCT images proved its feasibility,strong generalization,and robustness.

Fetal MRI Artifacts: Semi-Supervised Generative Adversarial Neural Network for Motion Artifacts Reducing in Fetal Magnetic Resonance Images

This study addresses challenges in fetal magnetic resonance imaging (MRI) related to motion artifacts, maternal respiration, and hardware limitations. To enhance MRI quality, we employ deep learning techniques, specifically utilizing Cycle GAN. Synthetic pairs of images, simulating artifacts in fetal MRI, are generated to train the model. Our primary contribution is the use of Cycle GAN for fetal MRI restoration, augmented by artificially corrupted data. We compare three approaches (supervised Cycle GAN, Pix2Pix, and Mobile Unet) for artifact removal. Experimental results demonstrate that the proposed supervised Cycle GAN effectively removes artifacts while preserving image details, as validated through Structural Similarity Index Measure (SSIM) and normalized Mean Absolute Error (MAE). The method proves comparable to alternatives but avoids the generation of spurious regions, which is crucial for medical accuracy.

Fiber swelling to improve cycle performance of paper-based separator for lithium-ion batteries application

It is well established that paper-based separators display short-circuit risk in lithium-ion batteries due to their intrinsic micron-sized pores.In this research,we have adjusted pore structure of paper by fiber swelling in liquid electrolyte.Specifically,the paper-based separator is prepared by propionylated sisal fibers through a wet papermaking process.Scanning electron microscope(SEM)and multi-range X-ray nano-computed tomography(CT)images display strong swelling of modified fibers after electrolyte absorption,which can effectively decrease the pore size of separator.Due to the high electrolyte uptake(817 wt%),paper-based separator exhibits ionic conductivity of 2.93 mS cm^(-1).^(7)Li solid-state NMR spectroscopy and Gaussian simulation reveal that the formation of local high Li^(+)ion concentration in the separator and its low absorption energy with Li^(+) ion(62.2 kcal mol^(-1))is conducive to the ionic transportation.In particular,the assembled Li/separator/LiFePO_(4) cell displays wide electrochemical stability window(5.2 V)and excellent cycle performance(capacity retention of 96.6%after 100 cycles at 0.5C)due to the reduced side reactions as well as enhanced electrolyte absorption and retention capacity by propionylation.Our proposed strategy will provide a novel perspective to design high-performance biobased separators to boost the development of clean and sustainable energy economy.

In Situ Directional Polymerization of Poly(1,3-dioxolane)Solid Electrolyte Induced by Cellulose Paper-Based Composite Separator for Lithium Metal Batteries

In traditional in situ polymerization preparation for solid-state electrolytes,initiators are directly added to the liquid precursor.In this article,a novel cellulose paper-based composite separator is fabricated,which employs alumina as the inorganic reinforcing material and is loaded with polymerization initiator aluminum trifluoromethanesulfonate.Based upon this,a separator-induced in situ directional polymerization technique is demonstrated,and the extra addition of initiators into liquid precursors is no longer required.The polymerization starts from the surface and interior of the separator and extends outward with the gradually dissolving of initiators into the precursor.Compared with its traditional counterpart,the separator-induced poly(1,3-dioxolane)electrolyte shows improved interfacial contact as well as appropriately mitigated polymerization rate,which are conducive to practical applications.Electrochemical measurement results show that the prepared poly(1,3-dioxolane)solid electrolyte possesses an oxidation potential up to 4.4 V and a high Li+transference number of 0.72.After 1000 cycles at 2 C rate(340 mA g^(−1)),the assembled Li||LiFePO_(4)solid battery possesses a 106.8 mAh g^(−1)discharge capacity retention and 83.5%capacity retention ratio,with high average Coulombic efficiency of 99.5%achieved.Our work may provide new ideas for the design and application of in situ polymerization technique for solid electrolytes and solid batteries.

Artifacts in two-dimensional shear wave elastography of liver

BACKGROUND Artifacts are common when using two-dimensional shear wave elastography(2-D SWE)to measure liver stiffness(LS),but they are poorly recognized.AIM To investigate the presence and influence of artifacts in 2-D SWE of liver.METHODS We included 158 patients with chronic liver disease,who underwent 2-D SWE examination by a novice and an expert.A cross line at the center of the elastogram was drawn and was divided it into four locations:top-left,top-right,bottom-left,and bottom-right.The occurrence frequency of artifacts in different locations was compared.The influence of artifacts on the LS measurements was evaluated by comparing the elastogram with the most artifacts(EMA)and the elastogram with the least artifacts(ELA).RESULTS The percentage of elastograms with artifacts in the novice(51.7%)was significantly higher than that of the expert(19.6%)(P<0.001).It was found that both operators had the highest frequency of artifacts at bottom-left,followed by top-left and bottom-right,and top-right had the lowest frequency.The LS values(LSVs)and standard deviation values of EMAs were significantly higher than those of ELAs for both operators.An intraclass correlation coefficient value of 0.96 was found in the LSVs of EMAs of the two operators,and it increased to 0.98 when the LSVs of the ELAs were used.Both operators had lower stability index values for EMAs than ELAs,but the difference was only statistically significant for the novice.CONCLUSION Artifacts are common when using 2-D SWE to measure LS,especially for the novice.Artifacts may lead to the overestimation of LS and reduce the repeatability and reliability of LS measurements.

Investigations of moiréartifacts induced by flux fluctuations in x-ray dark-field imaging

X-ray dark-field imaging using a grating interferometer has shown potential benefits for a variety of applications in recent years.X-ray dark-field image is commonly retrieved by using discrete Fourier transform from the acquired phasestepping data.The retrieval process assumes a constant phase step size and a constant flux for each stepped grating position.However,stepping errors and flux fluctuations inevitably occur due to external vibrations and/or thermal drift during data acquisition.Previous studies have shown that those influences introduce errors in the acquired phase-stepping data,which cause obvious moiréartifacts in the retrieved refraction image.This work investigates moiréartifacts in x-ray dark-field imaging as a result of flux fluctuations.For the retrieved mean intensity,amplitude,visibility and dark-field images,the dependence of moiréartifacts on flux fluctuation factors is theoretically derived respectively by using a first-order Taylor series expansion.Results of synchrotron radiation experiments verify the validity of the derived analytical formulas.The spatial frequency characteristics of moiréartifacts are analyzed and compared to those induced by phase-stepping errors.It illustrates that moiréartifacts can be estimated by a weighted mean of flux fluctuation factors,with the weighting factors dependent on the moiréphase and different greatly for each retrieved image.Furthermore,moiréartifacts can even be affected by object’s features not displayed in the particular contrast.These results can be used to interpret images correctly,identify sources of moiréartifacts,and develop dedicated algorithms to remove moiréartifacts in the retrieved multi-contrast images.

A MXene-functionalized paper-based electrochemical immunosensor for label-free detection of cardiac troponin I

Convenient,rapid,and accurate detection of cardiac troponin I(cTnI)is crucial in early diagnosis of acute myocardial infarction(AMI).A paper-based electrochemical immunosensor is a promising choice in this field,because of the flexibility,porosity,and cost-efficacy of the paper.However,paper is poor in electronic conductivity and surface functionality.Herein,we report a paper-based electrochemical immunosensor for the label-free detection of cTnI with the working electrode modified by MXene(Ti_(3)C_(2))nanosheets.In order to immobilize the bio-receptor(anti-cTnI)on the MXene-modified working electrode,the MXene nanosheets were functionalized by aminosilane,and the functionalized MXene was immobilized onto the surface of the working electrode through Nafion.The large surface area of the MXene nanosheets facilitates the immobilization of antibodies,and the excellent conductivity facilitates the electron transfer between the electrochemical species and the underlying electrode surface.As a result,the paper-based immunosensor could detect cTnI within a wide range of 5-100 ng/mL with a detection limit of 0.58 ng/mL.The immunosensor also shows outstanding selectivity and good repeatability.Our MXene-modified paper-based electrochemical immunosensor enables fast and sensitive detection of cTnI,which may be used in real-time and cost-efficient monitoring of AMI diseases in clinics.

Enhanced segmentation of gastrointestinal polyps from capsule endoscopy images with artifacts using ensemble learning

BACKGROUND Endoscopy artifacts are widespread in real capsule endoscopy(CE)images but not in high-quality standard datasets.AIM To improve the segmentation performance of polyps from CE images with artifacts based on ensemble learning.METHODS We collected 277 polyp images with CE artifacts from 5760 h of videos from 480 patients at Guangzhou First People’s Hospital from January 2016 to December 2019.Two public high-quality standard external datasets were retrieved and used for the comparison experiments.For each dataset,we randomly segmented the data into training,validation,and testing sets for model training,selection,and testing.We compared the performance of the base models and the ensemble model in segmenting polyps from images with artifacts.RESULTS The performance of the semantic segmentation model was affected by artifacts in the sample images,which also affected the results of polyp detection by CE using a single model.The evaluation based on real datasets with artifacts and standard datasets showed that the ensemble model of all state-of-the-art models performed better than the best corresponding base learner on the real dataset with artifacts.Compared with the corresponding optimal base learners,the intersection over union(IoU)and dice of the ensemble learning model increased to different degrees,ranging from 0.08%to 7.01%and 0.61%to 4.93%,respectively.Moreover,in the standard datasets without artifacts,most of the ensemble models were slightly better than the base learner,as demonstrated by the IoU and dice increases ranging from-0.28%to 1.20%and-0.61%to 0.76%,respectively.CONCLUSION Ensemble learning can improve the segmentation accuracy of polyps from CE images with artifacts.Our results demonstrated an improvement in the detection rate of polyps with interference from artifacts.

Reduction of artifacts in dental cone beam CT images to improve the three dimensional image reconstruction

Cone-beam CT (CBCT) scanners are based on volumetric tomography, using a 2D extended digital array providing an area detector [1,2]. Compared to traditional CT, CBCT has many advantages, such as less X-ray beam limitation, and rapid scan time, etc. However, in CBCT images the x-ray beam has lower mean kilovolt (peak) energy, so the metal artifact is more pronounced on. The position of the shadowed region in other views can be tracked by projecting the 3D coordinates of the object. Automatic image segmentation was used to replace the pixels inside the metal object with the boundary pixels. The modified projection data, using synthetically Radon Transformation, were then used to reconstruct a new back projected CBCT image. In this paper, we present a method, based on the morphological, area and pixel operators, which we applied on the Radon transformed image, to reduce the metal artifacts in CBCT, then we built the Radon back project images using the radon invers transformation. The artifacts effects on the 3d-reconstruction is that, the soft tissues appears as bones or teeth. For the preprocessing of the CBCT images, two methods are used to recognize the noisy black areas that the first depends on thresholding and closing algorithm, and the second depends on tracing boundaries after using thresholding algorithm too. The intensity of these areas is the lowest in the image than other tissues, so we profit this property to detect the edges of these areas. These two methods are applied on phantom and patient image data. It deals with reconstructed CBCT dicom images and can effectively reduce such metal artifacts. Due to the data of the constructed images are corrupted by these metal artifacts, qualitative and quantitative analysis of CBCT images is very essential.

A review of methods for mitigating ionospheric artifacts in differential SAR interferometry

Interferometric synthetic aperture radar(InSAR)has been widely used to measure ground displacements related to geophysical and anthropic activities over the past three decades.Satellite SAR systems use microwave signals that interact with the ionosphere when they travel through it during the imaging processes.In this context,ionospheric variations can significantly contaminate SAR imagery,which in turn affects spaceborne InSAR measurements.This bias also leads to a decrease in the coherence and accuracy of InSAR measurements,especially for the low-frequency SAR systems.In this paper,we give an overview of the latest methods for mitigating the ionospheric contributions in InSAR,including Faraday rotation method,azimuth shift method,and range split-spectrum method,and only focus on the single pair of InSAR interferograms.The current challenges and future perspectives are outlined at the end of this paper.

Determining the Authenticity of Artifacts by Oxygen Isotope Analysis

A technique used to determine the authenticity of artifacts that compares the oxygen isotopic composition of speleothems to the carbonate included within the patina of unprovenanced artifacts is of questionable value. The unprovenanced Jehoash Inscription Tablet and James Ossuary are of potentially immense historical and cultural importance. Nevertheless, they both were rejected by workers based on the oxygen isotope technique which provided the major foundational evidence of forgery in the longest running archaeological trial in Israel. Nevertheless, both these artifacts were determined not to be forged. The initial incongruence between the oxygen isotopes of the speleothems of the Soreq cave (Israel) purported to represent the unique composition of Jerusalem rainfall, and the patina on the artifacts, can be readily explained by the accretion of materials and geo-biochemical processes expected in normal patina formation in the Jerusalem region. The patina formation involves sporadic events in disequilibrium kinetic processes that are opposed to the equilibrium formation of speleothems in a sealed cave. Moreover, 23 of 56 patina samples (41%) on well-documented ancient artifacts from Israel yielded oxygen isotope values greater or lower than the expected speleothem values of -4 δ18O ‰ [PDB] to -6 δ18O ‰ [PDB]. Thus, the speleothem-patina correlation is invalid and the applied oxygen isotopes technique for determining the authenticity of patinas on artifacts is not a useful tool in the authentication of artifacts.

Facile Fabrication of Cellulosic Paper-based Composites with Temperature-controlled Hydrophobicity and Excellent Mechanical Strength

In this paper,we presented a novel strategy to employ a plantderived carbohydrate polymer,i.e.,cellulose,to prepare a hydrophobic composite.Cellulose was used as a scaffold,and ethylene-propylene side by side(ES)fiber was thermally melted and then coated on the cellulose surface to achieve hydrophobicity.Experimental results revealed that the thermocoating ES fibers greatly increased the water contact angle of the cellulose scaffold from 25°to 153°while simultaneously enhanced the wet tensile strength of the composite approximately 6.7-fold(drying temperature of 170℃)compared with the pure cellulose paper.In particular,compared with other related research,the prepared cellulose-based composite possessed excellent hydrophobicity and superior mechanical strength,which introduces a new chemical engineering approach to prepare hydrophobic cellulose-based functional materials.

Ring artifacts removal in X-ray-induced acoustic computed tomography

X-ray-induced acoustic computed tomography(XACT)is a hybrid imaging modality for detecting X-ray absorption distribution via ultrasound emission.It facilitates imaging from a single projection X-ray illumination,thus reducing the radiation exposure and improving imaging speed.Nonuniform detector response caused by the interference between multichannel data acquisition for ring array transducers and amplifier systems yields ring artifacts in the reconstructed XACT images,which compromises the image quality.We propose model-based algorithms for ring artifacts corrected XACT imaging and demonstrate their effcacy on numerical and experimental measurements.The corrected reconstructions indicate significantly reduced ring artifacts as compared to their conventional counterparts.

Investigation of artifacts by mapping SAR in thermoacoustic imaging

Microwave-induced thermoacoustic imaging(MI-TAI)remains one of the focus of attention among biomedical imaging modalities over the last decade.However,the transmission and dis-tribution of microwave inside bio-tissues are complicated,thus result in severe artifacts.In this study,to reveal the underlying mechanisms of artifacts,we deeply investigate the distribution of specific absorption rate(SAR)inside tissue-mimicking phantoms with varied morphological features using both mathematical simulations and corresponding experiments.Our simulated results,which are confirmed by the associated experimental results,show that the SAR distri-bution highly depends on the geometries of the imaging targets and the polarizing features of the microwave.In addition,we propose the potential mechanisms including Mie-scattering,Fabry-Perot-feature,small curvature effect to interpret the diffraction effect in different scenarios,which may provide basic guidance to predict and distinguish the artifacts for TAI in both fundamental and clinical studies.

Highly Improved Microstructure and Properties of Poly(p-phenylene terephthalamide) Paper-based Materials via Hot Calendering Process

In this study,the effect of hot calendering process on the microstructure and properties of poly(p-phenylene terephthalamide)(PPTA) paper-based materials was investigated.The microstructures of the fracture surface,crystalline structure,and single fiber strength of the PPTA paperbased materials as well as the different bonding behaviors between the PPTA fibers and PPTA fibrids obtained before and after the hot calendering process were examined.The results indicated that a high linear pressure would result in a limited improvement of the strength owing to the unimproved paper structure.The optimal values of tensile index and dielectric strength of 56.6 N·m/g and 27.6 kV/mm,respectively,could only be achieved with a synergistic effects of hot calendering temperature and linear pressure(240℃ and 110 k N/m,respectively).This result suggested it was possible to achieve a significant reinforcement and improvement in the interfacial bonding of functional PPTA paper-based materials,and avoid the formation of unexpected pleats and cracks in PPTA paper-based materials during the hot calendering process.

An adaptive fuzzy filter for coding artifacts removal in video and image

This paper proposes a new adaptive post-filtering algorithm to remove coding artifacts in block-based video coder. The proposed method concentrates on blocking and ringing artifacts removal. For de-blocking, the blocking strength is identified to determine the filtering range, and the maximum quantization parameter of the image is used to adapt the 1D fuzzy filter. For de-ringing, besides the edge detection, a complementary ringing detection method is proposed to locate the neglected ringing blocks, and the gradient threshold is adopted to adjust the parameter of 2D fuzzy filter. Experiments are performed on the MPEG-4 sequences. Compared with other methods, the proposed one achieves better detail preservation and artifacts removal performance with lower computational cost.

Fabrication of paper-based devices for in vitro tissue modeling

Paper devices have recently attracted considerable attention as a class of cost-effective cell culture substrates for various biomedical applications.The paper biomaterial can be used to partially mimic the in vivo cell microenvironments mainly due to its natural three-dimensional characteristic.The paper-based devices provide precise control over their structures as well as cell distributions,allowing recapitulation of certain interactions between the cells and the extracellular matrix.These features have shown great potential for the development of normal and diseased human tissue models.In this review,we discuss the fabrication of paper-based devices for in vitro tissue modeling,as well as the applications of these devices toward drug screening and personalized medicine.It is believed that paper as a biomaterial will play an essential role in the field of tissue model engineering due to its unique performances,such as good biocompatibility,eco-friendliness,cost-effectiveness,and amenability to various biodesign and manufacturing needs.

Determination of inhibitory activity of Salvia miltiorrhiza extracts on xanthine oxidase with a paper-based analytical device

A novel paper-based analytical device(PAD)was prepared and applied to determine the xanthine oxidase(XOD)inhibitory activity of Salvia miltiorrhiza extracts(SME).First,polycaprolactone was 3D printed on filter paper and heated to form hydrophobic barriers.Then the modified paper was cut according to the specific design.Necessary reagents including XOD for the colorimetric assay were immobilized on two separate pieces of paper.By simply adding phosphate buffer,the reaction was performed on the double-layer PAD.Quantitative results were obtained by analyzing the color intensity with the specialized device system(consisting of a smartphone,a detection box and sandwich plates).The 3Dprinted detection box was small,with a size of 9.0 cm×7.0 cm×11.5 cm.Color component G performed well in terms of linearity and detection limits and thus was identified as the index.The reaction conditions were optimized using a definitive screening design.Moreover,a 10%glycerol solution was found to be a suitable stabilizer.When the stabilizer was added,the activity of XOD could be maintained for at least 15 days under 4℃ or-20℃ storage conditions.The inhibitory activity of SME was investigated and compared to that of allopurinol.The results obtained with the PAD showed agreement with those obtained with the microplate method.In conclusion,the proposed PAD method is simple,accurate and has a potential for point-of-care testing.It also holds promise for use in rapid quality testing of medicinal herbs,intermediate products,and preparations of traditional Chinese medicines.

Artifacts Reduction Using Multi-Scale Feature Attention Network in Compressed Medical Images

Medical image compression is one of the essential technologies to facilitate real-time medical data transmission in remote healthcare applications.In general,image compression can introduce undesired coding artifacts,such as blocking artifacts and ringing effects.In this paper,we proposed a Multi-Scale Feature Attention Network(MSFAN)with two essential parts,which are multi-scale feature extraction layers and feature attention layers to efficiently remove coding artifacts of compressed medical images.Multiscale feature extraction layers have four Feature Extraction(FE)blocks.Each FE block consists of five convolution layers and one CA block for weighted skip connection.In order to optimize the proposed network architectures,a variety of verification tests were conducted using validation dataset.We used Computer Vision Center-Clinic Database(CVC-ClinicDB)consisting of 612 colonoscopy medical images to evaluate the enhancement of image restoration.The proposedMSFAN can achieve improved PSNR gains as high as 0.25 and 0.24 dB on average compared to DnCNNand DCSC,respectively.