Abstract: The electroencephalogram (EEG) is often contaminated by muscle artifacts. In this paper, a new method for muscle artifact removal in EEG is presented, based on canonical correlation analysis (CCA) as a blind source separation (BSS) technique. This method is demonstrated on a synthetic data set. The method outperformed a low-pass filter with different cutoff frequencies and an independent component analysis (ICA)-based technique for muscle artifact removal. In addition, the method is applied on a real ictal EEG recording contaminated with muscle artifacts. The proposed method removed successfully the muscle artifact without altering the recorded underlying ictal activity

Abstract: Removing the motion artifacts from measured photoplethysmography (PPG) signals is one of the important issues to be tackled for the accurate measurement of arterial oxygen saturation during movement. In this paper, the motion artifacts were reduced by exploiting the quasi-periodicity of the PPG signal and the independence between the PPG and the motion artifact signals. The combination of independent component analysis and block interleaving with low-pass filtering can reduce the motion artifacts under the condition of general dual-wavelength measurement. Experiments with synthetic and real data were performed to demonstrate the efficacy of the proposed algorithm.

Abstract: Independent component analysis (ICA) proves to be effective in the removing the ocular artifact from electroencephalogram recordings (EEG). While using ICA in ocular artifact correction, a crucial step is to correctly identify the artifact components among the decomposed independent components. In most previous works, this step of selecting the artifact components was manually implemented, which is time consuming and inconvenient when dealing with a large amount of EEG data. We present a new method which automatically selects the eye blink artifact components based on the pattern of their scalp topographies, which can be exemplified as a template matching approach. The feasibility of using a fixed template for singling out the eye blink component after ICA decomposition was validated by an experiment in which 18 subjects among the 21 subjects involved exhibited a highly consistent pattern of eye blink scalp topographies. Since only the spatial feature is employed for singling out the eye blink component, the proposed method is very efficient and easy to implement. Objective evaluation of the real results shows that the proposed algorithm can remove the eye blink artifact from the EEG while causing little distortion to the underlying brain activities.

Abstract: The Electroencephalogram (EEG) is a biological signal that represents the electrical activity of the brain. Eye-blinks and movement of the eyeballs produce electrical signals that are collectively known as Ocular Artifacts (OA). These are of the order of milli-volts and they contaminate the EEG signals which are of the order of micro-volts. The frequency range of EEG signal is 0 to 64 Hz and the OA occur within the range of 0 to 16 Hz. If the wavelet based EOG correction algorithm is applied to the entire length of the EEG signal, it results in thresholding of both low frequency and high frequency components even in the non-OA zones. This leads to considerable loss of valuable background EEG activity. Though the detection of OA zones can be done by visual inspection, the OA time zones need to be given as input to the EOG correction procedure, which is a laborious process. Hence there is a need for automatic detection of artifact zones. This paper discusses a method to automatically identify slow varying OA zones and applying wavelet based adaptive thresholding algorithm only to the identified OA zones, which avoids the removal of background EEG information. Adaptive thresholding applied only to the OA zone does not affect the low frequency components in the non-OA zones and also preserves the shape (waveform) of the EEG signal in non- artifact zones which is of very much importance in clinical diagnosis.

Abstract: Purpose The purpose of this study was to investigate the appearance and possible cause of an artifact seen in limited-volume cone-beam CT imaging. Methods A water-filled plastic cylinder was used as a phantom of the head. A test object was constructed as a bone-equivalent phantom to be imaged. The test object was variously positioned at the center of the phantom and near its margins. CT images of the test object were acquired using a 3DX Accuitomo system. Results In slice images with the test object positioned near the margin of the phantom, arch-shaped defects or deformities were observed on the side of the object. There was a negative correlation between the artifact and the CT value of the object. The artifact was larger in images scanned with a higher voltage. Conclusion The probability that this artifact is caused by halation from the image intensifier (II) system is suggested.

Abstract: The electrocardiogram (ECG) has been widely used for diagnosis purposes of heart diseases. Good quality ECG are utilized by the physicians for interpretation and identification of physiological and pathological phenomena. However, in real situations, ECG recordings are often corrupted by artifacts. One prominent artifact is the high frequency noise caused by electromyogram induced noise, power line interferences, or mechanical forces acting on the electrodes. Noise severely limits the utility of the recorded ECG and thus need to be removed for better clinical evaluation. Several methods have been developed for ECG denoising. In this paper, we proposed a new ECG denoising method based on the recently developed Empirical Mode Decomposition (EMD). The proposed EMD-based method is able to remove high frequency noise with minimum signal distortion. The method is validated through experiments on the MIT-BIH database. Both quantitative and qualitative results are given. The results show that the proposed method provides very good results for denoising.

Abstract: Simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) has been studied to identify areas related to EEG events. EEG data recorded in the magnetic resonance (MR) scanner with MR imaging is suffered from two specific artifacts, imaging artifact, and ballistocardiogram (BCG). In this paper, we focus on BCG. In preceding studies, average subtraction was often used for this purpose. However, average subtraction requires an assumption that BCG waveforms are precisely periodic, which seems unrealistic because BCG is a biomedical artifact. We propose the application of independent component analysis (ICA) with a postprocessing of high-pass filtering for the removal of BCG. With this approach, it is not necessary to assume that the BCG waveform is periodic. Empirically, we show that our proposed method removes BCG artifacts as well as does the average subtraction method. Power spectral density analysis of the two approaches shows that, with ICA, distortion of recovered EEG data is also as small as that associated with the average subtraction approach. We also propose a hypothesis for how head movement causes BCGs and show why ICA can remove BCG artifacts arising from this source.

Abstract: Electrodes and circuitry for monitoring and stimulating the exterior of the human body, comprising delivering stimulation pulses to stimulation electrodes applied to the exterior of the body, detecting an electrical potential at monitoring electrodes applied to the exterior of the body, positioning at least a first and second monitoring electrode at locations at which an electrical artifact caused by the electrical stimulation pulses is substantially cancelled in a signal formed from the electrical potentials detected at the first and second monitoring electrodes.

Abstract: The invention relates to a method and apparatus for detecting artifacts in a bioelectric signal, especially in a frontal EEG signal. In order to accomplish an uncomplicated mechanism for detecting artifacts in clinical applications, an impedance signal is measured through a first electrode set attached to the skin surface in a measurement area of a patient's body, the impedance signal being indicative of the impedance of the signal path formed between individual electrodes of the set. Simultaneously with the impedance measurement, a bioelectric signal is acquired through a second electrode set also attached to the skin surface of the measurement area, and the time periods are determined during which the impedance signal fulfills at least one predetermined criterion indicative of the presence of artifact in the bioelectric signal. In one embodiment, the first and second electrode sets are formed by a common set of two electrodes.

Abstract: The electrocardiogram (ECG) artifact is a major noise contaminating the myoelectric control signals when using shoulder disarticulation prosthesis This is an even more significant problem with targeted muscle reinnervation to develop additional myoelectric sites for improved prosthesis control in a bilateral amputee at shoulder disarticulation level This study aims at removal of ECG artifacts from the myoelectric prosthesis control signals produced from targeted muscle reinnervation Three ECG artifact removal methods based on template subtracting, wavelet thresholding and adaptive filtering were investigated, respectively Surface EMG signals were recorded from the reinnervated pectoralis muscles of the amputee As a key parameter for clinical myoelectric prosthesis control, the amplitude measurement of the signal was used as a performance indicator to evaluate the proposed methods The feasibility of the different methods for clinical application was also investigated with consideration of the clinical speed requirements and memory limitations of commercial prosthesis controllers

Abstract: Accuracy of a three-dimensional imaging system is improved through the use of model-based calibration and lookup tables to resolve distance according to, e.g., x-displacement, y-displacement, or image disparity data. In an embodiment, the lookup table(s) stores localized parameterization data used to calculate calibrated results.

Abstract: As the population of patients treated with deep brain stimulation (DBS) grows and the patients age, more will require routine or emergent electrophysiologic tests. DBS artifact may render these uninterpretable, whereas stopping DBS may release symptoms that confound evaluation. The authors find that monopolar, but not bipolar, stimulation produces significant artifact during EKG, EEG, and polysomnography.

Abstract: Magnetic distortions surrounding a typical brachytherapy seed (IMC6711, OncoSeed) within a clinical magnetic resonance imager were modeled for a number of different seed orientations with respect to the main magnetic field. From these distortion maps, simulated images were produced. The simulated images were then compared to images experimentally acquired using a spin echo technique on a Philips 1.5 T magnetic resonance imaging scanner. The modeled images were found to conform very well to those acquired experimentally, thus allowing one to establish where the seed is positioned within the complex image distortion patterns. The artifact patterns were dependent on the orientation of the seed with the main magnetic field, as well as the direction of the read encode gradient. While all imaging schemes which employ a unidirectional linear read encode trajectory should produce the artifacts modeled in this article, sequences other than spin echo may produce additional artifacts. Gradient echo and steady-state free precession imaging techniques were also performed on the seed for comparison.

Abstract: Eye blinking artifacts present serious problems for electroencephalographic (EEG) interpretation and analysis In this study, we apply independent component analysis (ICA) to eye blinking artifact removal from cognitive EEG recordings Due to the specific design of the experiment, the eye blinks almost always co-occur with the event-related potentials (ERP), which creates problems for ICA We introduced another data set of spontaneous blink and combined it with single-trial ERP data Our results show that ICA on the combined data set gives separation that makes more sense and makes it easier for EEG interpretation and analysis I INTRODUCTION lectroencephalographic (EEG) recordings are usually contaminated by eye movements, eye blinks, muscle activity and line noise These artifacts can be orders of magnitude larger than the signals of interest and may propagate across much of the scalp This poses a big problem if some properties (amplitude, latency, etc) of the signals are to be analyzed, which is common for event-related potentials (ERP) analysis Thus it is desirable to remove the artifacts as completely as possible without distorting the underlying brain signals

Abstract: The present invention relates to an improved method for the simultaneous calibration and qualification of a non-contact probe on a localizer using a single artifact, in which non-contact probe readings and localizer readings are synchronised using parameters determined simultaneously with calibration and qualification. The invention also relates to a non-contact probe and other devices, and a computer program for performing the invention.

Abstract: A method and apparatus for improving the quality of a composite video signal and a method and apparatus for decoding the composite video signal. The method for improving the quality of the composite video signal respectively detects edges from a luminance information signal and a chrominance information signal separated from the composite video signal, detects an artifact region using the detected edges, and filters the detected artifact region. Accordingly, an artifact can be effectively removed while preserving edge information and detail information of an image to improve picture quality.

Abstract: The electrocardiogram (ECG) has been widely used for diagnosis purposes of heart diseases. A good quality ECG may help the physicians to easily interpret any physiological or pathological phenomena. However, in real situations, ECG recordings are often affected by several factors that result in the baseline wander. Baseline wander is a low frequency artifact that may be due to respiration or the motion of the patients or the electrodes. A large baseline wander severely limits the utility of the recorded ECG and thus need to be corrected to enable better clinical evaluation. In this paper, we propose a new baseline wander correction method based on the recently developed tool-Empirical Mode Decomposition (EMD). We validate our method by experiments from the MIT-BIH databases and also compare our method with the highpass filtering method. Both qualitative and quantitative results show that the proposed EMD-based method provides very good results.

Abstract: The undersampled radial acquisition has been widely employed for accelerated (by a factor R = N(r)/N(p)) cardiac imaging, but the resulting reduction in image quality has not been well characterized. This investigation presents a method of measuring these artifacts through synthetic undersampling of high SNR images (SNR > or = 30). After validating the method in phantoms, the method was applied to a study of short-axis, long-axis, and coronary MRI imaging in healthy subjects. For 60 projections (60 N(p)), the total artifact is approximately 10% for short and long-axis imaging (R = 2.1) and approximately 15% for coronary MRI (R = 3.7). For 60 N(p), the SD of artifact in the region of the heart is 2% for short- and long-axis imaging (R = 2.1) and 3.5% for coronary MRI (R = 3.7). The artifact content is less in the region of the heart than in the periphery. The artifact is very reproducible among subjects for standard views. A study of coronary MRI at progressively fewer projections (at constant scan time) showed that right coronary MRI images were acceptable if total artifact was 120, R = 2.1).

Abstract: Multislice helical computed tomography (CT) is a promising noninvasive technique for coronary artery imaging. Various factors can cause inconsistencies in cardiac CT data, which can result in degraded image quality. These inconsistencies may be the result of the patient physiology (e.g., heart rate variations), the nature of the data (e.g., cone-angle), or the reconstruction algorithm itself. An algorithm which provides the best temporal resolution for each slice, for example, often provides suboptimal image quality for the entire volume since the cardiac temporal resolution (TRc) changes from slice to slice. Such variations in TRc can generate strong banding artifacts in multi-planar reconstruction images or three-dimensional images. Discontinuous heart walls and coronary arteries may compromise the accuracy of the diagnosis. A {beta}-blocker is often used to reduce and stabilize patients' heart rate but cannot eliminate the variation. In order to obtain robust and optimal image quality, a software solution that increases the temporal resolution and decreases the effect of heart rate is highly desirable. This paper proposes an ECG-correlated direct cone-beam reconstruction algorithm (TCOT-EGR) with cardiac banding artifact correction (CBC) and disconnected projections redundancy compensation technique (DIRECT). First the theory and analytical model of the cardiac temporal resolution is outlined. Next, themore » performance of the proposed algorithms is evaluated by using computer simulations as well as patient data. It will be shown that the proposed algorithms enhance the robustness of the image quality against inconsistencies by guaranteeing smooth transition of heart cycles used in reconstruction.« less

Abstract: This work explores an image-based approach for localizing needles during MRI-guided interventions, for the purpose of tracking and navigation. Susceptibility artifacts for several needles of varying thickness were imaged, in phantoms, using a 3 tesla MRI system, under a variety of conditions. The relationship between the true needle positions and the locations of artifacts within the images, determined both by manual and automatic segmentation methods, have been quantified and are presented here.

Abstract: The standardized OASIS Security Assertion Markup Language (SAML) has become one of the most deployed frameworks in federated identity management even though it focuses only on single sign-on. Answering industry’s pursuit of the reduction of user-management costs and enabling cost-efficient deployment because of its browser-based profiles, SAML is believed to become widely used soon. With the revision to Version 2.0, especially SAML’s browser/artifact profile has gained new security measures defeating old vulnerabilities. We analyze this profile and focus on the problem of artifact information flow. We devise a concrete exploit to demonstrate the impact of this problem. We address this problem by a new browser/artifact profile called Janus. The innovation is to split the artifact into two independent shares that have different information flow in a standard web browser. This new method defeats artifact information flow efficiently without relying on assumptions on the artifact lifetime.

Abstract: Figure 1 Three-dimensional reconstruction of the midline sagittal plane from an original axial plane at 27 weeks of gestation showing the hyperechogenic artifact described in the text. the corpus callosum is anechogenic or hypoechogenic and the presence of hyperechogenicity signifies possible pathology, mainly callosal lipoma. In a recent issue of the Journal, the use of threedimensional (3D) reconstruction of sagittal planes was proposed as an alterative method for the study of brain anatomy and particularly of midline structures2,3. Surprisingly, in the paper of Correa et al.2 and also in lectures presented by leading authorities in the field of 3D ultrasound, 3D reconstructed images depicted the corpus callosum as a hyperechogenic structure; Pilu et al.3