Showing papers on "Artifact (error) published in 2011"

ADJUST: An automatic EEG artifact detector based on the joint use of spatial and temporal features.

Abstract: A successful method for removing artifacts from electroencephalogram (EEG) recordings is Independent Component Analysis (ICA), but its implementation remains largely user-dependent. Here, we propose a completely automatic algorithm (ADJUST) that identifies artifacted independent components by combining stereotyped artifact-specific spatial and temporal features. Features were optimized to capture blinks, eye movements, and generic discontinuities on a feature selection dataset. Validation on a totally different EEG dataset shows that (1) ADJUST’s classification of independent components largely matches a manual one by experts (agreement on 95.2% of the data variance), and (2) Removal of the artifacted components detected by ADJUST leads to neat reconstruction of visual and auditory eventrelated potentials from heavily artifacted data. These results demonstrate that ADJUST provides a fast, efficient, and automatic way to use ICA for artifact removal. Descriptors: Electroencephalography, Independent component analysis, EEG artifacts, EEG artefacts, Event-related potentials, Ongoing brain activity, Automatic classification, Thresholding

ARTiiFACT: a tool for heart rate artifact processing and heart rate variability analysis

Abstract: The importance of appropriate handling of artifacts in interbeat interval (IBI) data must not be underestimated. Even a single artifact may cause unreliable heart rate variability (HRV) results. Thus, a robust artifact detection algorithm and the option for manual intervention by the researcher form key components for confident HRV analysis. Here, we present ARTiiFACT, a software tool for processing electrocardiogram and IBI data. Both automated and manual artifact detection and correction are available in a graphical user interface. In addition, ARTiiFACT includes time- and frequency-based HRV analyses and descriptive statistics, thus offering the basic tools for HRV analysis. Notably, all program steps can be executed separately and allow for data export, thus offering high flexibility and interoperability with a whole range of applications.

Imaging near metal with a MAVRIC-SEMAC hybrid.

Abstract: The recently developed multi-acquisition with variable resonance image combination (MAVRIC) and slice-encoding metal artifact correction (SEMAC) techniques can significantly reduce image artifacts commonly encountered near embedded metal hardware. These artifact reductions are enabled by applying alternative spectral and spatial-encoding schemes to conventional spin-echo imaging techniques. Here, the MAVRIC and SEMAC concepts are connected and discussed. The development of a hybrid technique that utilizes strengths of both methods is then introduced. The presented technique is shown capable of producing minimal artifact, high-resolution images near total joint replacements in a clinical setting.

Signal quality measures for pulse oximetry through waveform morphology analysis.

Abstract: Pulse oximetry has been extensively used to estimate oxygen saturation in blood, a vital physiological parameter commonly used when monitoring a subject's health status. However, accurate estimation of this parameter is difficult to achieve when the fundamental signal from which it is derived, the photoplethysmograph (PPG), is contaminated with noise artifact induced by movement of the subject or the measurement apparatus. This study presents a novel method for automatic rejection of artifact contaminated pulse oximetry waveforms, based on waveform morphology analysis. The performance of the proposed algorithm is compared to a manually annotated gold standard. The creation of the gold standard involved two experts identifying sections of the PPG signal containing good quality PPG pulses and/or noise, in 104 fingertip PPG signals, using a simultaneous electrocardiograph (ECG) signal as a reference signal. The fingertip PPG signals were each 1 min in duration and were acquired from 13 healthy subjects (10 males and 3 females). Each signal contained approximately 20 s of purposely induced artifact noise from a variety of activities involving subject movement. Some unique waveform morphology features were extracted from the PPG signals, which were believed to be correlated with signal quality. A simple decision-tree classifier was employed to arrive at a classification decision, at a pulse-by-pulse resolution, of whether a pulse was of acceptable quality for use or not. The performance of the algorithm was assessed using Cohen's kappa coefficient (κ), sensitivity, specificity and accuracy measures. A mean κ of 0.64 ± 0.22 was obtained, while the mean sensitivity, specificity and accuracy were 89 ± 10%, 77 ± 19% and 83 ± 11%, respectively. Furthermore, a heart rate estimate, extracted from uncontaminated sections of PPG, as identified by the algorithm, was compared with the heart rate derived from an uncontaminated simultaneous ECG signal. The mean error between both heart rate readings was 0.49 ± 0.66 beats per minute (BPM), in comparison to an error value observed without using the artifact detection algorithm of 7.23 ± 5.78 BPM. These results demonstrate that automated identification of signal artifact in the PPG signal through waveform morphology analysis is achievable. In addition, a clear improvement in the accuracy of the derived heart rate is also evident when such methods are employed.

Relationship Between Measurement Site and Motion Artifacts in Wearable Reflected Photoplethysmography

Abstract: Pulse rates obtained from wearable photoplethysmography (PPG) sensors are important for monitoring cardiovascular condition, especially during exercise. However, it is difficult to precisely count pulse rates during exercise because PPG is sensitive to body movement. The artifacts from body movement are caused by a change in the blood volume at the measurement site, in addition to pulsatile changes. Here, we investigated the influence of motion artifact with respect to light source and anatomical sites. In this study, we compared the signal from green-light PPG to that from infrared PPG at different anatomical sites. In these experiments, 11 subjects were asked to either assume a resting position or generate spontaneous motion artifact by jumping and swinging their arm. As a result, pulse rates obtained from green-light PPG showed a higher correlation with the ECG R-R interval as compared to those obtained with infrared. Additionally, the signal from the upper arm showed less artifact than did the peripheral one. Therefore, the green-light PPG may be useful for pulse rate monitoring.

Removal of large muscle artifacts from transcranial magnetic stimulation-evoked EEG by independent component analysis

Abstract: We present two techniques utilizing independent component analysis (ICA) to remove large muscle artifacts from transcranial magnetic stimulation (TMS)-evoked EEG signals. The first one is a novel semi-automatic technique, called enhanced deflation method (EDM). EDM is a modification of the deflation mode of the FastICA algorithm; with an enhanced independent component search, EDM is an effective tool for removing the large, spiky muscle artifacts. The second technique, called manual method (MaM) makes use of the symmetric mode of FastICA and the artifactual components are visually selected by the user. In order to evaluate the success of the artifact removal methods, four different quality parameters, based on curve comparison and frequency analysis, were studied. The dorsal premotor cortex (dPMC) and Broca’s area (BA) were stimulated with TMS. Both methods removed the very large muscle artifacts recorded after stimulation of these brain areas. However, EDM was more stable, less subjective, and thus also faster to use than MaM. Until now, examining lateral areas of the cortex with TMS—EEG has been restricted because of strong muscle artifacts. The methods described here can remove those muscle artifacts, allowing one to study lateral areas of the human brain, e.g., BA, with TMS—EEG.

Clinical ultrasound physics

Abstract: Understanding the basic physics of ultrasound is essential for acute care physicians. Medical ultrasound machines generate and receive ultrasound waves. Brightness mode (B mode) is the basic mode that is usually used. Ultrasound waves are emitted from piezoelectric crystals of the ultrasound transducer. Depending on the acoustic impedance of different materials, which depends on their density, different grades of white and black images are produced. There are different methods that can control the quality of ultrasound waves including timing of ultrasound wave emission, frequency of waves, and size and curvature of the surface of the transducer. The received ultrasound signal can be amplified by increasing the gain. The operator should know sonographic artifacts which may distort the studied structures or even show unreal ones. The most common artifacts include shadow and enhancement artifacts, edge artifact, mirror artifact and reverberation artifact.

Artifact and Recording Concepts in EEG

Abstract: Artifact is present when electrical potentials that are not brain derived are recorded on the EEG and is commonly encountered during interpretation. Many artifacts obscure the tracing, while others reflect physiologic functions that are crucial for routine visual analysis. Both physiologic and nonphysiologic sources of artifact may act as source of confusion with abnormality and lead to misinterpretation. Identifying the mismatch between potentials that are generated by the brain from activity that does not conform to a realistic head model is the foundation for recognizing artifact. Electroencephalographers are challenged with the task of correct interpretations among the many artifacts that could potentially be misleading, resulting in an incorrect diagnosis and treatment that may adversely impact patient care. Despite advances in digital EEG, artifact identification, recognition, and elimination are essential for correct interpretation of the EEG. The authors discuss recording concepts for interpreting EEG that contains artifact.

New MR imaging methods for metallic implants in the knee: artifact correction and clinical impact

Abstract: Purpose: To evaluate two magnetic resonance imaging (MRI) techniques, slice encoding for metal artifact correction (SEMAC) and multiacquisition variable-resonance image combination (MAVRIC), for their ability to correct for artifacts in postoperative knees with metal. Materials and Methods: A total of 25 knees were imaged in this study. Fourteen total knee replacements (TKRs) in volunteers were scanned with SEMAC, MAVRIC, and 2D fast spin-echo (FSE) to measure artifact extent and implant rotation. The ability of the sequences to measure implant rotation and dimensions was compared in a TKR knee model. Eleven patients with a variety of metallic hardware were imaged with SEMAC and FSE to compare artifact extent and subsequent patient management was recorded. Results: SEMAC and MAVRIC significantly reduced artifact extent compared to FSE (P < 0.0001) and were similar to each other (P = 0.58), allowing accurate measurement of implant dimensions and rotation. The TKRs were properly aligned in the volunteers. Clinical imaging with SEMAC in symptomatic knees significantly reduced artifact (P < 0.05) and showed findings that were on the majority confirmed by subsequent noninvasive or invasive patient studies. Conclusion: SEMAC and MAVRIC correct for metal artifact, noninvasively providing high-resolution images with superb bone and soft tissue contrast. J. Magn. Reson. Imaging 2011;33:1121–1127. © 2011 Wiley-Liss, Inc.

Boundary Artifact Reduction in View Synthesis of 3D Video: From Perspective of Texture-Depth Alignment

Abstract: 3D Video (3DV) with depth-image-based view synthesis is a promising candidate of next generation broadcasting applications. However, the synthesized views in 3DV are often contaminated by annoying artifacts, particularly notably around object boundaries, due to imperfect depth maps (e.g., produced by state-of-the-art stereo matching algorithms or compressed lossily). In this paper, we first review some representative methods for boundary artifact reduction in view synthesis, and make an in-depth investigation into the underlying mechanisms of boundary artifact generation from a new perspective of texture-depth alignment in boundary regions. Three forms of texture-depth misalignment are identified as the causes for different boundary artifacts, which mainly present themselves as scattered noises on the background and object erosion on the foreground. Based on the insights gained from the analysis, we propose a novel solution of suppression of misalignment and alignment enforcement (denoted as SMART) between texture and depth to reduce background noises and foreground erosion, respectively, among different types of boundary artifacts. The SMART is developed as a three-step pre-processing in view synthesis. Experiments on view synthesis with original and compressed texture/depth data consistently demonstrate the superior performance of the proposed method as compared with other relevant boundary artifact reduction schemes.

Diffusion Imaging with Prospective Motion Correction and Reacquisition

Abstract: A major source of artifacts in diffusion-weighted imaging (DWI) is subject motion. Slow bulk subject motion causes misalignment of data when more than one average or diffusion gradient direction is acquired. Fast bulk subject motion can cause signal dropout artifacts in diffusion-weighted images and results in erroneous derived maps e.g. fractional anisotropy maps. To address both types of artifacts, a fully automatic method is presented that combines prospective motion correction with a reacquisition scheme. Motion correction is based on the Prospective Acquisition Correction (PACE) method modified to work with diffusion-weighted data (DW-PACE). The images to reacquire are determined automatically during the acquisition from the imaging data i.e. no extra reference scan, navigators or external devices are necessary. The number of reacquired images i.e. the additional scan duration can be adjusted freely. DW-PACE corrects slow bulk motion well and reduces misalignment artifacts like image blurring. Mean absolute residual values for translation and rotation were less than 0.6 mm and 0.5 degrees. Reacquisition of images affected by signal dropout artifacts results in diffusion maps and fiber tracking free of artifacts. The presented method allows the reduction of two types of common motion related artifacts at the cost of slightly increased acquisition time.

A configurable and low-power mixed signal SoC for portable ECG monitoring applications

Abstract: This paper describes a mixed-signal ECG System-on-chip (SoC) that is capable of implementing configurable functionality with low-power consumption for portable ECG monitoring applications. A low-voltage and high performance analog front-end extracts 3-channel ECG signals and single channel impedance measurement with high signal quality. A custom digital signal processor provides the configurability and advanced functionality like motion artifact removal and R peak detection. The SoC is implemented in 0.18µm CMOS process and consumes minimum 31.1µW from a 1.2V.

Quantitative analysis of metallic artifacts caused by dental metals: comparison of cone-beam and multi-detector row CT scanners

Abstract: To quantitatively compare the streak artifacts produced by dental metals in a cone-beam computed tomography (CBCT) device and a multi-detector row computed tomography (MDCT) scanner in relation to metal types and imaging parameters. Cubes of aluminum, titanium, cobalt–chromium alloy, and type IV gold alloy were scanned with CBCT and MDCT scanners at tube voltages of 80 and 100 peak kV (kVp), and currents of 100 and 170 mAs by MDCT, and 102 and 170 mAs by CBCT. Artifact areas were quantified using ImageJ software. Artifact areas for the same metals and imaging parameters were smaller with CBCT than with MDCT under most conditions. Type IV gold alloy caused the largest artifact areas, followed by cobalt–chromium alloy, titanium, and aluminum, respectively. Higher tube voltage was associated with smaller artifact areas under most conditions, whereas increasing tube current had no consistent effect on artifact area using either CT device. CBCT was associated with smaller artifact areas than MDCT for the same parameters. Type IV gold alloy produced the largest artifact areas among the tested metals, but metallic artifacts could be reduced by increasing the tube voltage.

MuhRec—A new tomography reconstructor

Abstract: A new tool for computed tomography reconstruction is presented. The tool was developed to support the needs of users at neutron imaging beamlines and as a platform for algorithm development. It includes methods to handle large samples and artifact removal. The design is modular and allows tests of new concepts for preprocessing and back-projection. The reconstructor is tuned to provide the results fast even on a laptop computer. The reconstructor also has a graphical user interface which can be operated by new users after a short instruction.

Artifact management in rotational imaging

Abstract: A method for artifact management in a rotational imaging system is presented. The method includes the steps of acquiring data employing a helical scanning pattern over N revolutions, where N is greater than 1, and detecting at least one artifact in the acquired data of each revolution. The method further includes segmenting the data acquired over N revolutions into N-1 data frames each bounded by at least one of the at least one artifacts.

Standard artifact for the geometric verification of terrestrial laser scanning systems

Abstract: Terrestrial laser scanners are geodetic instruments with applications in areas such as architecture, civil engineering or environment. Although it is common to receive the technical specifications of the systems from their manufacturers, there are not any solutions for data verification in the market available for the users. This work proposes a standard artifact and a methodology to perform, in a simple way, the metrology verification of laser scanners. The artifact is manufactured using aluminium and delrin, materials that make the artifact robust and portable. The system consists of a set of five spheres situated at equal distances to one another, and a set of seven cubes of different sizes. A coordinate measuring machine with sub-millimetre precision is used for calibration purposes under controlled environmental conditions. After its calibration, the artifact can be used for the verification of metrology specifications given by manufacturers of laser scanners. The elements of the artifact are destinated to test different metrological characteristics, such as accuracy, precision and resolution. The distance between centres of the spheres is used to obtain the accuracy data, the standard deviation of the top face of the largest cube is used to establish the precision (repeatability) and the error in the measurement of the cubes provides the resolution value in axes X , Y and Z . Methodology for the evaluation is mainly supported by least squares fitting algorithms developed using Matlab programming. The artifact and methodology proposed were tested using a terrestrial laser scanner Riegl LMSZ-390i at three different ranges (10, 30 and 50 m) and four stepwidths (0.002°, 0.005°, 0.010° and 0.020°), both for horizontal and vertical displacements. Results obtained are in agreement with the accuracy and precision data given by the manufacturer, 6 and 4 mm, respectively. On the other hand, important influences between resolution and range and between resolution and stepwidth are observed. For example, the two smaller cubes cannot be well detected in any case and, as must be expected, the increase in range and stepwidth produces a decrease in the quality of the detection for the larger ones.

Spin-history artifact during functional MRI: potential for adaptive correction.

Abstract: Purpose: Functional magnetic resonance imaging (fMRI) is limited by sensitivity to millimetre-scale head motion. Adaptive correction is a strategy to adjust the imaging plane in response to measured head motion, thereby suppressing motion artifacts. This strategy should correct for motion in all six degrees of freedom and also holds promise for through-plane motion that creates “spin-history” artifact that cannot easily be removed by postprocessing methods. Improved quantitative understanding of the MRI signal behavior associated with spin-history artifact would be useful for implementing adaptive correction robustly. Methods: A numerical simulation was developed to predict MRI artifact signal amplitude in a single-slice for simple motions, implemented with and without adaptive correction, and compared with experiment by imaging a phantom at 3.0 T. Functional MRI was also performed of a human volunteer to illustrate adaptive correction in the presence of spin-history artifact. Results: Good agreement was achieved between simulation and experimental results. Although time-averaged artifact signal amplitude was observed to correlate linearly with motion speed, artifact time-courses were nonlinearly related to motion waveforms. In addition, experimental results demonstrated effective adaptive correction of spin-history artifact when the phantom underwent complex motions. Adaptive correction during human fMRI suppressed spin-history artifacts and spurious activations associated with task-correlated motion. Conclusions: Overall, this work suggests that adaptive correction, especially when implemented with minimal lag between motion measurement and scan plane update, may help to expand the populations for which fMRI can be performed robustly.

A wavelet based technique for suppression of EMG noise and motion artifact in ambulatory ECG

Abstract: A wavelet-based denoising technique is investigated for suppressing EMG noise and motion artifact in ambulatory ECG. EMG noise is reduced by thresholding the wavelet coefficients using an improved thresholding function combining the features of hard and soft thresholding. Motion artifact is reduced by limiting the wavelet coefficients. Thresholds for both the denoising steps are estimated using the statistics of the noisy signal. Denoising of simulated noisy ECG signals resulted in an average SNR improvement of 11.4 dB, and its application on ambulatory ECG recordings resulted in L 2 norm and max-min based improvement indices close to one. It significantly improved R-peak detection in both the cases.

Controlling access to sensitive data based on changes in information classification

Abstract: A Data Loss Prevention (DLP) system includes an automated method for tracking changes to a security classification (e.g., content category) associated with an artifact to determine whether an attempt is being made to subvert a DLP policy. The method exploits the basic principle that, depending on context, the classification of a particular artifact, or a change to an existing classification, may indicate an attempt to subvert the policy. According to the method, an artifact classification state machine is implemented within a DLP system. For each policy-defined content category on each artifact, the machine identifies a content category change that may be of interest, as defined by policy. When a change in a classification has occurred, an artifact notification event (or, more generally, a notification of the change in classification) is issued.

Motion artifacts associated with in vivo endoscopic OCT images of the esophagus

Abstract: 3-D optical coherence tomography (OCT) has been extensively investigated as a potential screening and/or surveillance tool for Barrett’s esophagus (BE). Understanding and correcting motion artifact may improve image interpretation. In this work, the motion trace was analyzed to show the physiological origin (respiration and heart beat) of the artifacts. Results showed that increasing balloon pressure did not sufficiently suppress the physiological motion artifact. An automated registration algorithm was designed to correct such artifacts. The performance of the algorithm was evaluated in images of normal porcine esophagus and demonstrated in images of BE in human patients.

Motion artifact reduction in ambulatory ECG monitoring: an integrated system approach

Abstract: Recent advances in low-power micro-electronics are revolutionizing ECG monitoring. Wearable patches now allow comfortable monitoring over several days. Achieving reliable and high integrity recording however remains a challenge, especially under daily-life activities. In this paper we present a system approach to motion artifact reduction in ambulatory recordings. A custom ultra-low-power ECG analog front-end read-out for simultaneous measurement of ECG and electrode-tissue impedance, from the same electrode, is reported. Integrating this front-end, we describe a wireless patch for the monitoring of 3-lead ECG, electrode electrical artifact and 3D-acceleration. Beyond ECG monitoring, this wireless patch provides the additional necessary data to filter out motion artifact. Two algorithm methods are tested. The first method applies ICA for de-noising multi-lead ECG recordings. The second method is an adaptive filter that uses skin/electrode impedance as the measurement of noise. Algorithms, circuits and system provide a platform for reliable ECG monitoring on-the-move.

Artifact analysis and image enhancement in three-dimensional computational integral imaging using smooth windowing technique

Abstract: We propose an artifact analysis in computational integral imaging and the image enhancement method based on the analysis using the smooth windowing technique. Blurring and lenslet artifacts, which are major problems in computational integral imaging, are defined and analyzed using a signal model. Applying a smooth and continuous window such as the triangular window to computational integral imaging reconstruction provides a dramatic improvement in terms of image quality. Experimental results are presented to show the validity of our method. To our best knowledge, this is the first trial to control a window function in computational integral imaging.

An ECG patch combining a customized ultra-low-power ECG SoC with Bluetooth low energy for long term ambulatory monitoring

Abstract: This paper presents the development of an ECG patch aiming at long term patient monitoring. The use of the recently standardized Bluetooth Low Energy (BLE) technology, together with a customized ultra-low-power ECG System on Chip (ECG SoC). including Digital Signal Processing (DSP) capabilities, enables the design of ultra low power systems able to continuously monitor patients, performing on board signal processing such as filtering, data compression, beat detection and motion artifact removal along with all the advantages provided by a standard radio technology such as Bluetooth. Early tests show how combining the ECG SoC and BLE leads to a total current consumption of only 500μA at 3.7V, while computing beat detection and transmitting heart rate remotely via BLE. This allows up to one month lifetime with a 400mAh Li-Po battery.

Robust Eye Movement Recognition Using EOG Signal for Human-Computer Interface

Abstract: Electrooculography (EOG) signal is one of the useful biomedical signals. Development of EOG signal as a control signal has been paid more increasing interest in the last decade. In this study, we are proposing a robust classification algorithm of eight useful directional movements that it can avoid effect of noises, particularly eye-blink artifact. Threshold analysis is used to detect onset of the eye movements. Afterward, four beneficial time features are proposed that are peak and valley amplitude positions, and upper and lower lengths of two EOG channels. Suitable threshold conditions were defined and evaluated. From experimental results, optimal threshold values were selected for each parameters and classification accuracies approach to 100% for three subjects testing. To avoid the eye-blink artifact, the first derivative was additionally implemented.