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.

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.

Removal of Ocular Artifacts from Electroencephalo-Graph by Improving Variational Mode Decomposition

Ocular artifacts in Electroencephalography(EEG)recordings lead to inaccurate results in signal analysis and process.Variational Mode Decomposition(VMD)is an adaptive and completely nonrecursive signal processing method.There are two parameters in VMD that have a great influence on the result of signal decomposition.Thus,this paper studies a signal decomposition by improving VMD based on squirrel search algorithm(SSA).It’s improved with abilities of global optimal guidance and opposition based learning.The original seasonal monitoring condition in SSA is modified.The feedback of whether the optimal solution is successfully updated is used to establish new seasonal monitoring conditions.Opposition-based learning is introduced to reposition the position of the population in this stage.It is applied to optimize the important parameters of VMD.GOSSA-VMD model is established to remove ocular artifacts from EEG recording.We have verified the effectiveness of our proposal in a public dataset compared with other methods.The proposed method improves the SNR of the dataset from-2.03 to 2.30.

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.

Method for predicting motion artifacts of plasma display panels

A simulation method is proposed to predict the motion artifacts of plasma display panels （PDPs）. The method simulates the behavior of the human vision system when perceiving moving objects. The simulation is based on the measured temporal light properties of the display for each gray level and each phosphor. Both the effect of subfield arrangement and phosphor decay are involved. A novel algorithm is proposed to improve the calculation speed. The simulation model manages to predict the appearance of the motion image perceived by a human with a still image. The results are validated by a set of perceptual evaluation experiments. This rapid and accurate prediction of motion artifacts enables objective characterization of the PDP performance in this aspect.

基于弗洛凯特理论的Halo轨道辐轮构型编队控制设计

面向未来使用平动点航天器编队进行深空探测的需求,研究了特殊的定向辐轮构型航天器编队在日地L2平动点Halo轨道上的动力学和相关控制问题。首先,建立了圆型限制性三体问题(CRTBP)的相对动力学和辐轮构型编队模型的数学表达;其次,基于Floquet理论和傅里叶级数展开推导了Halo轨道的相对运动解析解,该解的推导同样可应用于其他小偏离的周期时变系统;接着,以深空探测任务为导向,基于Floquet模态法和LQR控制法分别给出编队主星和从星的分层控制策略;最后,对控制策略进行仿真,详细分析了辐轮构型维持控制力的规律等,得到了构型参数(半径和频率)与维持代价的关系。

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.

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.

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.

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.

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.

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.

地月周期轨道对地月L1与L2附近Halo轨道的可见性分析

随着去往月球航天器的增多,现有的近地空间光学卫星与地基光学望远镜的探测能力已无法满足要求,急需增强地月空间观测能力,通过使用地月周期轨道来填补地月空间观测能力的不足被认为是一种有效手段。针对地月周期轨道的特性,文章基于微分校正原理对三体轨道建模,并完成了算法的设计,提出了地月周期轨道的选择原则,并优选了3条轨道。在地月周期轨道对地月拉格朗日点L1、L2附近Halo轨道的可见性分析中,为方便评估,采用类球体的物体星等评估模型来定义可见性的评估标准;基于卫星工具包提供模型计算中涉及的自然天体、物体和观测卫星三者的时空关系,给出了可见性分析过程及结果,研究表明地月周期轨道对地月拉格朗日点L1、L2附近Halo轨道均有不错的观测效果,其中轨道1对地月周期轨道的可见性综合最高,均大于95%。

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.

Sing Your City: Local Stories of Global Artifacts

The article discusses five local stories that, without being connected to each other, tell about the socio-cultural circumstances accompanying creation of works of art that have received significant (but not the highest) recognition on a global scale. The discussion concerns three songs about cities: Torna a Surriento, Moscow Nights, and Li Beirut;a famous Soviet painting Low Marks Again;and the design features of Audi cars for the US market over the past decade. The approach to each certain artifact, be it song, painting, or the design of rear turn signals, is developed on the basis of disciplinary affiliation, whereas a discipline is more sociology, anthropology, or history of an appropriate art, than its theory. Another research method places a local context into the test tube of globalization. Experience shows that these two methods are applicable to different arts, places, and periods enriching the scientist with more detailed information about the era studied.

最佳Halo重力牵引治疗Lenke3型脊柱侧凸的生物力学分析

背景:Halo重力牵引是许多学者认可的术前牵引方法,但大部分为临床观察,缺乏有限元的相关分析。目的:运用有限元法探究Halo重力牵引对Lenke3型脊柱侧凸的最佳牵引力,从生物力学角度为临床提供理论依据。方法:对脊柱侧凸患者扫描的CT图像进行逆向建模处理并建立有限元模型,并取正常节段(T1-T4椎体)对模型的有效性进行验证。对腰胸椎侧凸模型设置5组不同的受力条件,模拟患者在不同牵引力作用下的矫正情况。5组皆将L5下表面完全约束,在T1上表面施加沿Z轴正方向(重力的反方向)不同大小的牵引力,分别为50,100,150,200,250 N。对比不同牵引力下侧凸脊柱的位移、主弯曲的Cobb角变化情况、脊柱的伸长量以及Von Mises应力。结果与结论:①当Halo重力牵引力为150-200 N时,主弯曲的Cobb角缩小量为最大缩小量的69.4%-88.9%,Z轴的伸长量是最大伸长量69.4%-85.9%,受到的应力为最大应力的63.6%-82.9%;②牵引力大于200 N,Cobb角的减少量和Z轴的伸长量变化不明显,但应力值急剧增长,且此时的T6、T7、T8椎体质心到L5中垂线的减小距离最为明显;③当Halo重力牵引力为150-200 N时,对此类型患者的矫正效果最佳——Cobb角缩小量与Z轴伸长量效果较佳的同时不会有应力的急剧增长。上述结果可为临床矫正提供一定的理论支持,可在较大程度矫正侧凸时保证患者安全。

Score based assessment of implant-related post fusion MRI artifacts focused on different interbody disc spacers: An <i>in vitro</i>study

Interbody disc spacers for anterior spine fusion are made of different materials, such as titanium alloys or carbon fiber reinforced polymers (CFRP). Implant-related susceptibility artifacts can decrease the quality of MRI scans. This cadaveric study aimed to demonstrate the extent that implant-related MRI artifacting affects the post fusion differentiation of the spinal canal (SC) and intervertebral disc space (IDS). In 6 cadaveric porcine spines, we evaluated the post-im- plantation MRI scans of a titanium and CFRP spacer that differed in shape and surface qualities. A spacer made of human cortical bone was used as a control. A defined evaluation unit was divided into regions of interest (ROI) to characterize the SC and IDS. Considering 15 different MRI sequences read independently by an interobserver-validated team of specialists artifact-affected image quality of the median MRI slice was rated on a modified score of 0-1-2-3. A maximum score of 15 points for the SC and 9 points for the IDS (100%) was possible. Turbo spin echo sequences produced the best scores for both spacers and the control. Only the control achieved a score of 100%. For the IDS the titanium and CFRP spacer maximally scored 0% and 74%, for the SC 80% and 99%, respectively. By using favored T1 TSE sequences the CFRP-spacer represented clear advantages in post fusion spinal imaging. Independent of artifact dimensions the used scoring system allowed us to create an implant-related ranking of MRI scan quality in reference to the bone control.

Influences of Motion Artifacts on Three-Dimensional Reconstruction Volume and Conformal Radiotherapy Planning

Objective ：To investigate the influences of motion artifacts on three-dimensional （3D） reconstruction volume and conformal radiotherapy planning. Methods： A phantom which can mimic the clip motion of lung tumor along the cranial-caudal direction is constructed by step motor, small ball of polyethylene and potato. Ten different scan protocols were set and CT data of the phantom were acquired by using a commercial GE LightSpeedl6 CT scanner. The 3D reconstruction of the CT data was implemented by adopting volume-rendering technology of GE AdvantageSim 6.0 system. The reconstructed volumes of each target in different scan protocols were measured through 3D measuring tools. Thus, relative deviations of the reconstruction volumes between moving targets and static ones were determined. The three-dimensional conformal radiation therapy （3D- CRT） plans and conformal fields were created and compared for a static/moving target with the WiMRT treatment planning system （TPS）. Results：For a static target, there was no obvious difference among the 3D reconstruction volumes when the CT data were acquired with different pitches and slices. The appearance of 3D reconstruction volume and 3D conformal field of a moving target was quite different from that of static one. The maximum relative deviation is nearly 90% for a moving target scanned with different scan protocols. The relative deviations are variable among the different targets, about from -39.8% to 89.5% for a smaller target and from - 18.4% to 20.5% for a larger one. Conclusion ：The motion artifacts have great effects on 3 D-CRT planning and reconstruction volume, which will greatly induce distorted conformal radiation fields and false DVHs for a moving target.

微流星体碰撞对日地L_(2)点Halo轨道的影响

空间中存在大量高速运动的微流星体,与在轨运行的航天器发生碰撞后将导致轨道偏离、性能下降、结构破坏甚至航天器失效.由于Halo轨道具有不稳定的特性,本文主要探究微流星体碰撞对日地L_(2)点Halo轨道动力学演化规律的影响.首先,建立日地L_(2)点附近轨道的动力学模型,通过微分修正法构造Halo轨道的初始条件,基于Grün微流星体通量模型计算微流星体与航天器碰撞的数量和碰撞引起的速度改变量.然后,采用Runge-Kutta算法求解Halo轨道的动力学方程,研究碰撞速度改变量引起的轨道偏差随时间的演化规律.此外,采用状态转移矩阵方法分析初始状态偏差的演化规律,并与数值积分方法对比.最后基于状态转移矩阵方法分析了不同碰撞速度改变量的大小和方向引起的动力学响应.研究发现,状态转移矩阵在短时间内得到的结果与数值积分方法基本一致,而且只需一次矩阵乘法即可通过初始状态偏差计算得到末时刻状态偏差,具有非常高的效率.研究结果表明,由于Halo轨道固有的不稳定特性,所以初始时刻微流星体碰撞引起的微小状态偏差会快速增长,导致消耗更多控制燃料,最终将影响航天器的寿命.此外,微流星体碰撞的速度改变量的方向对偏差传递的规律有重要的影响.