Artifact Patterns Research Articles

The K8 House: A new domestic space from the Iron Age II at Tell Halif, Israel

ABSTRACTIn the Iron Age II period of the southern Levant (1000–586 BCE), most data for household studies come from four-room or pillared houses. Tell Halif in southern Israel gives us several examples of the four-room pillared house, including the one identified here as the K8 House, from the eighth century. The purpose of this research is to examine the K8 archaeological remains and add to our understanding of Iron Age houses and households as reflected in the patterning of artefacts in the buildings occupied by the household. Based on the remains preserved in the K8 House, we can identify a set of activities undertaken regularly inside the house. It can be demonstrated from Tell Halif’s archaeological data that, once the specific activities are identified, their organisation also can be identified. In order to understand how space functioned in the K8 House at Tell Halif, a spatial analysis of the archaeological materials was undertaken. Ceramics and microartefacts discovered on floors and in the covering fill provide important sources of data serving to identify activities and helping to assess what type of reductions of the ‘de facto’ refuse may have taken place. The locations of artefacts in the K8 House help to identify activity areas within it.

A new iterative algorithm for ring artifact reduction in CT using ring total variation.

In computed tomography (CT), miscalibrated or imperfect detector elements produce stripe artifacts in the sinogram. The stripe artifacts in Radon space are responsible for concentric ring artifacts in the reconstructed images. In this work, a novel optimization model is proposed to remove the ring artifacts in an iterative reconstruction procedure. In the proposed optimization model, a novel ring total variation (RTV) regularization is developed to penalize the ring artifacts in the image domain. Moreover, to correct the sinogram, a new correcting vector is proposed to compensate for malfunctioning of detectors in the projection domain. The optimization problem is solved by using the alternating minimization scheme (AMS). In each iteration, the fidelity term along with the RTV regularization is solved using the alternating direction method of multipliers (ADMM) to find the image, and then the correcting coefficient vector is updated for certain detectors according to the obtained image. Because the sinogram and the image are simultaneously updated, the proposed method basically performs in both image and sinogram domains. The proposed method is evaluated using both simulated and physical phantom datasets containing different ring artifact patterns. In the simulated datasets, the Shepp-Logan phantom, a real chest scan image and a noisy low-contrast phantom are considered for the performance evaluation of our method. We compare the quantitative root mean square error (RMSE) and structural similarity (SSIM) results of our algorithm with wavelet-Fourier sinogram filtering method by Munch et al., the ring artifact reduction method by Brun et al., and the TV-based ring correction method by Paleo and Mirone. Our proposed method is also evaluated using a physical phantom dataset where strong ring artifacts are manifest due to the miscalibration of a large number of detectors. Our proposed method outperforms the competing methods in terms of both qualitative and quantitative evaluation results. The experimental results in both simulated and physical phantom datasets show that the proposed method achieves the state-of-the-art ring artifact reduction performance in terms of RMSE, SSIM, and subjective visual quality.

An Online Spectral Information-Enhanced Approach for Artifact Detection and Fault Attentuation in Myoelectric Control.

In myocontrol of neuroprosthetic devices, multichannel electromyography (EMG) can be used to decode the intended motor command, based on distributed activation patterns of stump muscles. In this regard, the high density EMG (HD-EMG) approach allows for enhancement of the spatiotemporal resolution for motor intention detection. Despite the advantages of relying on several EMG channels, the challenge of high-density electrode systems is the dynamically changing electrode-skin contact impedance, which can affect a considerable number of electrodes over the time of data acquisition. This can result in obtaining unreliable, low-quality EMG recording with a distributed artifact pattern over the grid of EMG sensors. To address this issue, we propose a novel online approach for adaptive information extraction and enhancement for automatic artifact detection and attenuation in HD-EMG-based myocontrol of prosthetic devices. The method is based on an adaptive weighting scheme that modifies the contribution of each HD-EMG channel considering the spectral information content relative to artifacts. The technique (named IE-HD-EMG) was tested as an online pre-conditioning step for a challenging multiclass classification problem of 4-finger activation, using linear discriminant analysis. It is shown that for this application, the proposed IE-HD-EMG technique led to a superior performance in finger activation recognition (79.25% accuracy, 89% sensitivity, 89.15% specificity) in comparison to the conventional HD-EMG recording under the same condition without the proposed approach (56.25% accuracy, 61.3% sensitivity, 67% specificity). Therefore, the proposed technique can have a significant potential to expand the clinical viability of HD-EMG systems.

Three-dimensional Automated Breast US: Facts and Artifacts.

As automated breast (AB) US becomes more integrated into the daily practice of breast imaging, the need to address the artifacts that interfere with AB US image interpretation is becoming more important. Learning methods to detect and subsequently resolve artifacts such as shadowing can enhance the reader's confidence and ability to differentiate artifacts and true abnormalities. Understanding the basic principles of AB US and its image acquisition process are key elements in resolving artifacts. Gaining familiarity with the common patterns of AB US artifacts and placing them into categories of technical, software, physiologic, and breast lesion-related causes can aid in image interpretation. Recognizing specific artifacts, such as dropout and lack of contact, and the ability to distinguish them from true abnormalities, such as surgical scars and suspicious lesions, can help minimize preventable false-positive interpretations. Applying methods to confirm shadowing as artifactual, including the use of a second view, additional planes, and software-related tools such as the rotational tool, can aid the radiologist in resolving artifacts and avoiding preventable recalls, potentially resulting in increased specificity. Presented is a methodical approach to recognizing AB US artifacts and their causes; analyzing shadowing, a challenging entity in the interpretation of AB US imaging studies; differentiating artifact from true abnormality; and reviewing characteristic patterns and basic techniques to resolve artifacts. The goal of this article is to enable the radiologist in applying these methods to help reduce preventable false-positive recommendations and increase efficiency in AB US image interpretation. Online supplemental material is available for this article. ©RSNA, 2019.

Evaluation of a Commercial Ballistocardiography Sensor for Sleep Apnea Screening and Sleep Monitoring.

There exists a technological momentum towards the development of unobtrusive, simple, and reliable systems for long-term sleep monitoring. An off-the-shelf commercial pressure sensor meeting these requirements is the Emfit QS. First, the potential for sleep apnea screening was investigated by revealing clusters of contaminated and clean segments. A relationship between the irregularity of the data and the sleep apnea severity class was observed, which was valuable for screening (sensitivity 0.72, specificity 0.70), although the linear relation was limited ( of 0.16). Secondly, the study explored the suitability of this commercial sensor to be merged with gold standard polysomnography data for future sleep monitoring. As polysomnography (PSG) and Emfit signals originate from different types of sensor modalities, they cannot be regarded as strictly coupled. Therefore, an automated synchronization procedure based on artefact patterns was developed. Additionally, the optimal position of the Emfit for capturing respiratory and cardiac information similar to the PSG was identified, resulting in a position as close as possible to the thorax. The proposed approach demonstrated the potential for unobtrusive screening of sleep apnea patients at home. Furthermore, the synchronization framework enabled supervised analysis of the commercial Emfit sensor for future sleep monitoring, which can be extended to other multi-modal systems that record movements during sleep.

The Generation of Rifaat Al-Chaderchi Facades Using Standard Shape Grammars

The architecture of Rifaat Al-Chaderchi is of a distinct particularity with easily distinguished façades, which were artistically composed from rich traditional architectural elements and forms. He was one of the first Iraqi architects to experience the trend of critical regionalism as his works exhibit the interaction between the local traditions of Iraq and Western influences. On the other hand, shape grammar is of great importance in the field of architecture as it provides a fruitful approach for the study and analysis of the formal patterns of different artifacts belonging to certain architectural styles or architects. The current research focuses on the problem of studying the shape grammars of the architectural facades of Al-Chaderchi. It aims at defining the rules of the shape grammars that produced the form of those facades. Thus, the significance of this research stems from the disclosure of the shape rules that underlie the design of Al-Chaderchi facades and providing the possibility for re-application of the derived rules to generate those facades with the synthetic properties and formal relationships that distinguish certain facade from the others. The research adopts the method of standard shape grammars concerned with the structural and formal relationships of the façades compositions and their differences regardless the different criteria and dimensions associated with each facade. The research aim was achieved by the conclusion of the shape rules through which the facades of Al-Chaderchi have been composed. Then, the concluded rules were applied firstly, to derive those facades and secondly, to derive new facades that carry the same formal and elemental structure to test their application potentialities.

Meta-analysis of community’s adaptation pattern with tidal flood in Pekalongan City, Central Java, Indonesia

In the last two decades, northern coast Java Island occasionally experienced a tidal flood. One of area that affected by tidal flood is Pekalongan City, a small city in Central Java. Many studies have been conducted to investigate this issue. The area of investigation includes physical damage and people’s adaptation with tidal flood. This paper tries to explore people’s adaptation pattern in Pekalongan City with tidal flood. The meta-analysis approach was adopted as there are many papers that had investigated this phenomenon. This paper shows that community’s adaptation patterns in Pekalongan city tidal flood are divided into two response patterns, cognitive map and artifact patterns. These patterns have produced a new way of life or culture in the community. By understanding how people adaptation with tidal flood, hopefully, scientist and policymaker can bring more appropriate solution or policy to help people’s adaptation with tidal flood or how they minimize tidal flood effect in more sustainable way.

DiODe: Directional Orientation Detection of Segmented Deep Brain Stimulation Leads: A Sequential Algorithm Based on CT Imaging

Background: Directional deep brain stimulation (DBS) allows steering the stimulation in an axial direction which offers greater flexibility in programming. However, accurate anatomical visualization of the lead orientation is required for interpreting the observed stimulation effects and to guide programming. Objectives: In this study we aimed to develop and test an accurate and robust algorithm for determining the orientation of segmented electrodes based on standard postoperative CT imaging used in DBS. Methods: Orientation angles of directional leads (Cartesia^TM; Boston Scientific, Marlborough, MA, USA) were determined using CT imaging. Therefore, a sequential algorithm was developed that quantitatively compares the similarity of the observed CT artifacts with calculated artifact patterns based on the lead’s orientation marker and a geometric model of the segmented electrodes. Measurements of seven ground truth phantoms and three leads with 60 different configurations of lead implantation and orientation angles were analyzed for validation. Results: The accuracy of the determined electrode orientation angles was –0.6 ± 1.5° (range: –5.4 to 4.2°). This accuracy proved to be sufficiently high to resolve even subtle differences between individual leads. Conclusions: The presented algorithm is user independent and provides highly accurate results for the orientation of the segmented electrodes for all angular constellations that typically occur in clinical cases.

Gadolinium contrast medium administration does not adversely affect T2*-weighted gradient recalled echo magnetic resonance imaging of the canine brain at 1.5 Tesla.

As gadolinium-based contrast agents are paramagnetic and have T2 shortening effects, they have the potential to adversely affect gradient recalled echo sequences. The aim of this prospective, cross-sectional study was to evaluate the effects of gadolinium administration on T2*-weighted sequence diagnostic quality and signal intensity when imaging the canine brain. A total of 100 dogs underwent brain magnetic resonance imaging (MRI) including pre- and postcontrast T2*-weighted sequences acquired with a delay (Group A) or immediately (Group B) following gadolinium administration. Pre- and postcontrast images were subjectively compared. In dogs with intracranial enhancing masses, regions of interest were drawn on corresponding images and signal intensity ratios were calculated. The effect of degree and pattern of contrast enhancement, susceptibility artifacts, and time between contrast injection and T2*-weighted sequence acquisition on signal intensity ratio was evaluated. Overall 31 dogs had contrast enhancing intracranial masses. Subjectively, there was no difference in image quality of T2*-weighted sequences obtained before and after contrast medium administration. No significant signal intensity differences of intracranial contrast enhancing masses were found (Group A P=0.9999; Group B P=0.9992). Susceptibility artifacts did not differ in appearance, and there was no effect on calculated signal intensity ratio (P=0.8142). Similarly, there was no effect of degree of enhancement or contrast heterogeneity on signal intensity ratio (P=0.4413). No correlation was found between signal intensity ratio and the time to acquisition (P=0.199). Administration of gadolinium-based MRI contrast agents does not adversely affect T2*-weighted imaging of the brain in dogs at 1.5T even in the presence of contrast enhancing lesions.

Broken points and social cohesion in Iroquoian villages: A point refit study

Understanding patterns of artifact mends within a site has the potential to provide insights into human behavior. In this study, we map the distribution of projectile point mends at a mid-sixteenth century Iroquoian village in western New York. It is assumed that these point fragments were once embedded in meat and were discarded when the meat was consumed. As a result, the distribution of most point mends can be explained through waste stream analysis. However, those mends that occur over long distances or between different longhouses require another explanation. We propose that in these cases meat sharing between domestic groups occurred, as one mechanism used to cement interpersonal relationships. Long distance mends between potsherds and smoking pipes require additional explanations.

Deep learning with domain adaptation for accelerated projection-reconstruction MR.

PurposeThe radial k‐space trajectory is a well‐established sampling trajectory used in conjunction with magnetic resonance imaging. However, the radial k‐space trajectory requires a large number of radial lines for high‐resolution reconstruction. Increasing the number of radial lines causes longer acquisition time, making it more difficult for routine clinical use. On the other hand, if we reduce the number of radial lines, streaking artifact patterns are unavoidable. To solve this problem, we propose a novel deep learning approach with domain adaptation to restore high‐resolution MR images from under‐sampled k‐space data.MethodsThe proposed deep network removes the streaking artifacts from the artifact corrupted images. To address the situation given the limited available data, we propose a domain adaptation scheme that employs a pre‐trained network using a large number of X‐ray computed tomography (CT) or synthesized radial MR datasets, which is then fine‐tuned with only a few radial MR datasets.ResultsThe proposed method outperforms existing compressed sensing algorithms, such as the total variation and PR‐FOCUSS methods. In addition, the calculation time is several orders of magnitude faster than the total variation and PR‐FOCUSS methods. Moreover, we found that pre‐training using CT or MR data from similar organ data is more important than pre‐training using data from the same modality for different organ.ConclusionWe demonstrate the possibility of a domain‐adaptation when only a limited amount of MR data is available. The proposed method surpasses the existing compressed sensing algorithms in terms of the image quality and computation time.

Decoding non-linearity for effective extraction of the eye-blink artifact pattern from EEG recordings

• Effective extraction of ocular artifact by combining non-linear kernels with EEMD. • Maximize the extracted artifact and minimize the distortion in the brain signal. • The proposed method outperforms wavelet and EEMD with linear kernel based approach. Electroencephalogram (EEG) is a non-invasive measurement of electrical signal on the scalp originated due to neuronal activity. EEG signals associated with cortical activity are orders of magnitude lower in amplitude compared to other parasitic signals such as eye-blink artifacts , which contaminate the recorded EEG data making it imperative for the investigators to adopt an effective artifact suppression strategy. In all the previous studies, suppression of the pattern related to the artifacts was performed based on the assumption of a linear interaction between the source of artifact (eye-blink) and the brain signal (EEG data). This paper presents a novel methodology by considering the non-linear interaction between the artifact signal associated with the eye-blink and the contaminated EEG data using kernel functions . In the present work, adaptive data-driven approach called Ensemble Empirical Mode Decomposition (EEMD) is hybridized with kernel Principal Component Analysis (kPCA) to decode the non-linear interaction. The contaminated segment of EEG data is decomposed by the EEMD technique into a series of basic building blocks called intrinsic mode functions (IMFs). The features of the eye-blink signals are captured by some of these IMFs; subsequently, effective extraction of the ocular artifact from the IMFs is performed by kPCA using non-linear kernel functions (radial basis function, second and third-order polynomial function). In the present study, technique used for artifact suppression relies on the extraction of ocular artifact signal from IMFs based on optimizing the different parameters of the kPCA. Compared with other techniques used in previous studies, the proposed method (based on third-order polynomial kernel function) is capable of effectively extracting the pattern related to the ocular artifacts from the single channel contaminated EEG data with low distortion of the EEG signal.

Imagining the cultural landscapes of Paleoindians

Archaeologists commonly use the geographic patterning of sourced artifacts to understand how prehistoric cultures used their landscapes, yet exactly what this patterning indicates remains unclear. The Paleoindian literature reflects a tendency to assume that toolstone conveyance reflects direct acquisition (i.e., mobility) motivated by subsistence and technological concerns, rather than acquisition (i.e., exchange) motivated by social concerns. This tendency demonstrates a willingness on the part of many archaeologists to imagine Paleoindians organized on a physical landscape defined by the location of important material resources (e.g., food, water, stone), but a hesitancy to imagine Paleoindians organized on a social landscape defined by the location of other people. Yet the challenge of actually distinguishing between mobility and exchange persists. Here, I offer some ideas that might help us make headway on the linkage problem we confront when attempting to infer mode of acquisition from patterns of toolstone conveyance, focusing on the North American Great Basin. I imagine a Paleoindian cultural landscape defined, not just by the distribution of food and non-food resources, but also other people, to propose that mobility and exchange both contributed to the patterns of toolstone conveyance we see, perhaps operating at different scales in relation to subsistence, technological, and social motivations.

Reverberation and multiple shadow artifacts recorded from patients with intra‐pericardial centrifugal continuous‐flow left ventricular assist devices

Artifacts are by-products of ultrasound imaging that may cause confusion or misdiagnosis if not interpreted correctly. There are, however, several disorders where a specific pattern of artifacts can aid in diagnosis, especially when the object in question cannot be visualized directly. In this manuscript, we report two patients with reverberation and shadow artifacts originating from the housing and the propeller of a continuous-flow intra-pericardial left ventricular assist device. Visualization of the artifacts required modified transthoracic views, so these artifacts should not pose a diagnostic challenge during a routine echocardiographic evaluation. However, we consider that shadow artifacts might be used to evaluate pump thrombosis in patients with intra-pericardial assist devices.

Physical activity classification using time-frequency signatures of motion artifacts in multi-channel electrical impedance plethysmographs.

Physical activities are known to introduce motion artifacts in electrical impedance plethysmographic (EIP) sensors. Existing literature considers motion artifacts as a nuisance and generally discards the artifact containing portion of the sensor output. This paper examines the notion of exploiting motion artifacts for detecting the underlying physical activities which give rise to the artifacts in question. In particular, we investigate whether the artifact pattern associated with a physical activity is unique; and does it vary from one human-subject to another? Data was recorded from 19 adult human-subjects while conducting 5 distinct, artifact inducing, activities. A set of novel features based on the time-frequency signatures of the sensor outputs are then constructed. Our analysis demonstrates that these features enable high accuracy detection of the underlying physical activity. Using an SVM classifier we are able to differentiate between 5 distinct physical activities (coughing, reaching, walking, eating and rolling-on-bed) with an average accuracy of 85.46%. Classification is performed solely using features designed specifically to capture the time-frequency signatures of different physical activities. This enables us to measure both respiratory and motion information using only one type of sensor. This is in contrast to conventional approaches to physical activity monitoring; which rely on additional hardware such as accelerometers to capture activity information.

Ultrasonographic Images of Nasal Bone Fractures with Water Used as the Coupling Medium.

Background:Ultrasonography can show local and superficial fractures of the nasal bone. However, it is difficult to see the whole nasal bone. We used water as the coupling medium for ultrasonography.Methods:This method was used in 76 nasal bone fracture cases from July 2011 to March 2013, and we could obtain clear images of the entire nasal bone and surrounding bones. However, in some images, there were artifacts and blurred areas. The patterns of blurring were classified and their causes were analyzed.Results:The 6 patterns of artifacts and blurred images were (1) Blurred side wall of the nasal bone in 68 cases, (2) air bubbles in the water in 68 cases, (3) unclear deep portions by attenuation in 23 cases, (4) distorted images caused by shaking of the probe in 44 cases, (5) parallel shadows due to multiple reflections in 18 cases, and (6) mysterious shadows caused by side lobes of the ultrasound beams in 55 cases. Almost all of them could be avoided by adding some small changes of techniques.Conclusions:Our methods can provide whole clear images of the nasal bone and surrounding bones in 1 field. Almost all the artifacts and blurred images which occurred during the performance of our methods could be avoided by adding some small changes, for example, tilting the probe, pouring the water slowly, and moving the probe closer to the nose.

Computational simulations of the influence of background noise removal in optical-CT imaging of gel dosimeters

Background noise removal is an easy way to diminish the impact of imperfect signals in the projection blank regions in optical CT imaging of gel dosimeters. The influence of this approach to reconstruction accuracy and noise behaviour is assessed by computational simulations using synthetic phantoms. The results show that an offset is induced in the reconstructed phantom region by background noise removal, but the amplitude of the offset is negligible. Also, no apparent noise or artefact patterns are noticeable. We can conclude that the background noise removal method doesn’t impact the reconstruction accuracy of filtered backprojection reconstruction algorithm for optical CT imaging.

A Channel Rejection Method for Attenuating Motion-Related Artifacts in EEG Recordings during Walking.

Recording scalp electroencephalography (EEG) during human motion can introduce motion artifacts. Repetitive head movements can generate artifact patterns across scalp EEG sensors. There are many methods for identifying and rejecting bad channels and independent components from EEG datasets, but there is a lack of methods dedicated to evaluate specific intra-channel amplitude patterns for identifying motion-related artifacts. In this study, we proposed a template correlation rejection (TCR) as a novel method for identifying and rejecting EEG channels and independent components carrying motion-related artifacts. We recorded EEG data from 10 subjects during treadmill walking. The template correlation rejection method consists of creating templates of amplitude patterns and determining the fraction of total epochs presenting relevant correlation to the template. For EEG channels, the template correlation rejection removed channels presenting the majority of epochs (>75%) correlated to the template, and presenting pronounced amplitude in comparison to all recorded channels. For independent components, the template correlation rejection removed components presenting the majority of epochs correlated to the template. Evaluation of scalp maps and power spectra confirmed low neural content for the rejected components. We found that channels identified for rejection contained ~60% higher delta power, and had spectral properties locked to the gait phases. After rejecting the identified channels and running independent component analysis on the EEG datasets, the proposed method identified 4.3 ± 1.8 independent components (out of 198 ± 12) with substantive motion-related artifacts. These results indicate that template correlation rejection is an effective method for rejecting EEG channels contaminated with motion-related artifact during human locomotion.

Air and its Sonographic Appearance: Understanding the Artifacts

BackgroundAlthough air has traditionally been considered a barrier to sonographic imaging, when encountered in unusual settings it can serve as an important indicator of various pathologic states as well. Clinician recognition and thorough understanding of the characteristic pattern of artifacts generated by air are critical for making a number of important diagnoses. Case SeriesWe present five emergency department cases in which air was visualized in a pathologic location. Pneumothorax, pneumoperitoneum, necrotizing fasciitis, or Fournier's gangrene, and subcutaneous emphysema and pneumomediastinum, can be rapidly and easily identified on ultrasound by the presence of air artifacts. The relevant sonographic findings are described and discussed in this article. Why Should an Emergency Physician Be Aware of This?Due to its inherent impedance mismatch with other human tissues, air has a characteristic appearance on ultrasound that includes irregular hyperechoic structures, “dirty shadowing,” A-lines, and decreased visualization of deeper structures. Knowledge of the sonographic appearance of air artifacts can assist the physician in making a diagnosis, selecting appropriate additional imaging, and enlisting specialist consultation.

Artifacts in histology: A 1-year retrospective study

Introduction: Histology is a science of the analysis of tissue architecture; however, the presence of artifacts in microscopic sections may result in misdiagnosis. Despite documented common occurrences, studies on the patterns of artifacts in Nigeria are however scant. The rarity of descriptions in this clumsy but important component of histology stimulated our interest in demonstrating the various patterns of artifacts in a laboratory. This 1-year retrospective study was conducted in Federal Medical Centre, Asaba, Delta State. Materials and Methods: Tissue sections were viewed and with the aid of a microscope to check for the various patterns of artifacts. These artifacts were seen as artificial structures or tissue alternations on the prepared slide. Histological images were captured using eyepiece Scopetek DCM 500, 5.0 Megapixel connected USB 2.0 computer. Data were obtained by standard microscopic techniques in which the various patterns of tissue alterations were described. Permission for this study was obtained from the hospital Ethics Committee (ethical number FMC/ASB/T/A81/198). Results: This review of patterns of artifacts showed that during the 1-year period, of the 388 slides reviewed, 94.59% had the presence of artifacts. The results also revealed that fold artifacts were the most prevalent patterns constituting about 33.00% of the total tissue sections observed, followed by artifacts attributed to microtomy which accounted for 18.47% and formalin pigment artifacts, 14.78%. The least was heat and hemorrhagic artifacts which contributed to about 0.25%. Conclusion: In conclusion, fold artifacts were the most prevalent patterns observed in this study due to the thin sections which easily stretch around other structures having different constituencies if the tissue is not carefully lifted from the water bath.