Showing papers on "Artifact (error) published in 2003"

An adaptive spatial fuzzy clustering algorithm for 3-D MR image segmentation

Abstract: An adaptive spatial fuzzy c-means clustering algorithm is presented in this paper for the segmentation of three-dimensional (3-D) magnetic resonance (MR) images. The input images may be corrupted by noise and intensity nonuniformity (INU) artifact. The proposed algorithm takes into account the spatial continuity constraints by using a dissimilarity index that allows spatial interactions between image voxels. The local spatial continuity constraint reduces the noise effect and the classification ambiguity. The INU artifact is formulated as a multiplicative bias field affecting the true MR imaging signal. By modeling the log bias field as a stack of smoothing B-spline surfaces, with continuity enforced across slices, the computation of the 3-D bias field reduces to that of finding the B-spline coefficients, which can be obtained using a computationally efficient two-stage algorithm. The efficacy of the proposed algorithm is demonstrated by extensive segmentation experiments using both simulated and real MR images and by comparison with other published algorithms.

Temporally constrained ICA: an application to artifact rejection in electromagnetic brain signal analysis

Abstract: Independent component analysis (ICA) is a technique which extracts statistically independent components from a set of measured signals. The technique enjoys numerous applications in biomedical signal analysis in the literature, especially in the analysis of electromagnetic (EM) brain signals. Standard implementations of ICA are restrictive mainly due to the square mixing assumption-for signal recordings which have large numbers of channels, the large number of resulting extracted sources makes the subsequent analysis laborious and highly subjective. There are many instances in neurophysiological analysis where there is strong a priori information about the signals being sought; temporally constrained ICA (cICA) can extract signals that are statistically independent, yet which are constrained to be similar to some reference signal which can incorporate such a priori information. We demonstrate this method on a synthetic dataset and on a number of artifactual waveforms identified in multichannel recordings of EEG and MEG. cICA repeatedly converges to the desired component within a few iterations and subjective analysis shows the waveforms to be of the expected morphologies and with realistic spatial distributions. This paper shows that cICA can be applied with great success to EM brain signal analysis, with an initial application in automating artifact extraction in EEG and MEG.

Respiratory motion artifacts on PET emission images obtained using CT attenuation correction on PET-CT

Abstract: PET-CT scanners allow generation of transmission maps from CT. The use of CT attenuation correction (CTAC) instead of germanium-68 attenuation correction (Ge AC) might be expected to cause artifacts on reconstructed emission images if differences in respiratory status exist between the two methods of attenuation correction. The aim of this study was to evaluate for possible respiratory motion artifacts (RMA) in PET images attenuation corrected with CT from PET-CT in clinical patients. PET-CT scans were performed using a Discovery LS PET-CT system in 50 consecutive patients (23 males, 27 females; mean age 58.2 years) with known or suspected malignancy. Both CTAC and Ge AC transmission data obtained during free tidal breathing were used to correct PET emission images. Cold artifacts at the interface of the lungs and diaphragm, believed to be due to respiratory motion (RMA), that were seen on CTAC images but not on the Ge AC images were evaluated qualitatively on a four-point scale (0, no artifact; 1, mild artifact; 2, moderate artifact; 3, severe artifact). RMA was also measured for height. Curvilinear cold artifacts paralleling the dome of the diaphragm at the lung/diaphragm interface were noted on 84% of PET-CT image acquisitions and were not seen on the 68Ge-corrected images; however, these artifacts were infrequently severe. In conclusion, RMA of varying magnitude were noted in most of our patients as a curvilinear cold area at the lung/diaphragm interface, but were not diagnostically problematic in these patients.

Independent component analysis as a tool to eliminate artifacts in EEG: a quantitative study.

Abstract: Independent component analysis (ICA) is a novel technique that calculates independent components from mixed signals. A hypothetical clinical application is to remove artifacts in EEG. The goal of this study was to apply ICA to standard EEG recordings to eliminate well-known artifacts, thus quantifying its efficacy in an objective way. Eighty samples of recordings with spikes and evident artifacts of electrocardiogram (EKG), eye movements, 50-Hz interference, muscle, or electrode artifact were studied. ICA components were calculated using the Joint Approximate Diagonalization of Eigen-matrices (JADE) algorithm. The signal was reconstructed excluding those components related to the artifacts. A normalized correlation coefficient was used as a measure of the changes caused by the suppression of these components. ICA produced an evident clearing-up of signals in all the samples. The morphology and the topography of the spike were very similar before and after the removal of the artifacts. The correlation coefficient showed that the rest of the signal did not change significantly. Two examiners independently looked at the samples to identify the changes in the morphology and location of the discharge and the artifacts. In conclusion, ICA proved to be a useful tool to clean artifacts in short EEG samples, without having the disadvantages associated with the digital filters. The distortion of the interictal activity measured by correlation analysis was minimal.

Electrode systems and methods for reducing motion artifact

Abstract: An electrode system for reducing noise from an electronic signal, the system including an electrode that provides the electronic signal, and a sensor that senses motion and provides a motion signal. The electrode system includes a controller that determines a noise value based on an analysis of the motion signal, and subtracts the noise value from the electronic signal. The electrode system can reduce or eliminate motion artifact from an electronic signal that can result in misdiagnosis, prolong procedural duration and inappropriate treatment of a patient.

Parametric error modeling and software error compensation for rapid prototyping

Abstract: This paper is motivated by the need for a generic approach to evaluate the volumetric accuracy of rapid prototyping (RP) machines The approach presented in this paper is inspired in large part by the techniques developed over the years for the parametric evaluation of coordinate measuring machine (CMM) errors In CMM metrology, the parametric error functions for the machine are determined by actual measurement of a master reference artifact with known characteristics In our approach, the RP machine is used to produce a generic artifact, which is then measured by a master CMM, and measurement results are used to infer the RP machine's parametric error functions The results presented demonstrate the feasibility of such an approach on a two‐dimensional model

Automated statistical self-calibrating detection and removal of blemishes in digital images based on determining probabilities based on image analysis of single images

Abstract: A method of automatically correcting dust artifact within images acquired by a system including a digital camera includes determining probabilities of dust artifact regions corresponding to pixels within a digitally-acquired image based at least in part on a pixel analysis of the region in view of predetermined characteristics indicative of the presence of a dust artifact region. The dust artifact regions are associated with one or more extracted parameters relating to the optical system when the image was acquired. A statistical dust map is formed including mapped dust regions based on the dust artifact determining and associating operations. Digital data is corrected corresponding to correlated dust artifact regions within the acquired image based on the associated statistical dust map.

Method and apparatus for performing neuroimaging

Abstract: The present invention relates to systems and methods of performing magnetic resonance imaging (MRI) in awake animals. The invention utilizes head and body restrainers to position an awake animal relative to a radio frequency dual coil system operating in a high field magnetic resonance imaging system to provide images of high resolution without motion artifact.

A simple system for detection of EEG artifacts in polysomnographic recordings

Abstract: We present an efficient parametric system for automatic detection of electroencephalogram (EEG) artifacts in polysomnographic recordings. For each of the selected types of artifacts, a relevant parameter was calculated for a given epoch. If any of these parameters exceeded a threshold, the epoch was marked as an artifact. Performance of the system, evaluated on 18 overnight polysomnographic recordings, revealed concordance with decisions of human experts close to the interexpert agreement and the repeatability of expert's decisions, assessed via a double-blind test. Complete software (Matlab source code) for the presented system is freely available from the Internet at http://brain.fuw.edu.pl/artifacts.

Artifact removal from an electric signal

Abstract: The invention relates to a method and apparatus for suppressing interference in an electric signal, particularly for suppressing interference in an electrocardiogram (ECG) signal in connection with magnetic resonance imaging (MRI). In order to improve the accuracy of the suppression, the electric signal is first sampled at a high sampling frequency, whereby a first sequence of samples is obtained. Some of the samples in the first sequence of samples are then selected on the basis of predetermined criteria. The first sequence is then downsampled using the selected samples, whereby a second sequence of samples is obtained. The second sequence forms a digital presentation of the electric signal in which the interference is suppressed.

Automatic optimization methods and systems for doppler ultrasound imaging

Abstract: Methods and systems are provided for automatic optimization of spectral Doppler ultrasound imaging. One or more of the velocity scale (e.g., pulse repetition frequency), gain, baseline, dynamic range or other imaging parameters are optimized based on one or both of: (1) determining the optimum parameter based on data acquired at a standard or predetermined setting of the parameters and (2) identifying an artifact in the Doppler ultrasound data and discarding or minimizing the influence of the artifact on any determination of imaging parameter settings. One embodiment used for cardiac Doppler imaging identifies artifact signals using the maximum or minimum traces. For example, the velocity scale or pulse repetition frequency is set based on the maximum or minimum velocity value over one or more heartbeats identified from a maximum and minimum trace of the signal envelope or Doppler spectrum. Since flows in cardiology may contain high energy, high velocity, short duration signals caused by valve clicks, these artifacts are identified and discarded in determining the maximum and minimum values.

Modification of red-eye-effect in digital image

Abstract: In one aspect, the present disclosure describes a process for automatic artifact compensation in a digital representation of an image. The process includes detecting, by a processor, regions corresponding to facial images within the digital representation; locating, by the processor, red-eye regions within the detected regions; and automatically modifying, by the processor, the located red-eye regions to provide a modified image.

EEG ocular artifact removal through ARMAX model system identification using extended least squares

Abstract: The removal of ocular artifact from scalp electroencephalograms (EEGs) is of con- siderable importance for both the automated and visual analysis of underlying brainwave activity. Traditionally, subtraction techniques use linear regression to estimate the influence of eye movements on the electrodes of interest. These methods are based on the assumption that the underlying brain- wave activity is uncorrelated when, in general, it is not. Furthermore, regression methods assume that the ocular artifact propagation is frequency independent, i.e. all waveforms of the ocular artifact propagate similarly. In this paper, we examine relaxing these assumptions by using a more general autoregressive (AR) moving average (MA) exogenous (X) model and the extended least squares (ELS) algorithm to remove ocular artifact. We demonstrate that in some cases this general ARMAX model can decrease ocular artifact not removable by standard regression techniques. We also show that the incorporation of a forgetting factor to exponentially weight past data can improve ocular artifact removal even for the traditional subtraction method.

On the artifact of a subvoxel susceptibility deviation in spoiled gradient-echo imaging.

Abstract: In MRI, susceptibility-based negative contrast amplifies the effect of objects that are too small to be detected by water displacement or intrinsic contrast properties. In this work, a simplified description of the susceptibility artifact of a subvoxel object in spoiled gradient-echo imaging is presented that focuses on the elimination of signal in its vicinity: the dephased-volume. The size and position of the dephased-volume are investigated using 3D time-domain simulations and in vitro experiments in which scan parameters and object magnetic moment are systematically varied. Overall signal loss is found to be linearly related to a dephasing parameter that contains the susceptibility difference with tissue, object volume, and echo time (TE), and thus allows the magnetic moment of the object to be assessed. Gradient strength, in-plane resolution, fractional echo, and slice orientation have limited influence. For the settings used, the center of mass of the artifact was always within 0.5 mm of the object's in-plane position.

Enabling computer decisions based on EEG input

Abstract: Multilayer neural networks were successfully trained to classify segments of 12-channel electroencephalogram (EEG) data into one of five classes corresponding to five cognitive tasks performed by a subject. Independent component analysis (ICA) was used to segregate obvious artifact EEG components from other sources, and a frequency-band representation was used to represent the sources computed by ICA. Examples of results include an 85% accuracy rate on differentiation between two tasks, using a segment of EEG only 0.05 s long and a 95% accuracy rate using a 0.5-s-long segment.

Method for the calibration and qualification simultaneously of a non-contact probe

Abstract: The present invention relates to a method for calibrating a non-contact probe on a localizer. The present further relates to a method for the simultaneous calibration and qualification of a non-contact probe on a localizer. Both methods do not require user intervention, and use a single artifact.

Windmill artifact in multislice helical CT

Abstract: Multi-slice helical CT-systems suffer from windmill artifacts: black/white patterns that spin off of features with high longitudinal gradients. The number of black/white pairs matches the number of slices (detector rows) in the multi-slive detector. The period of spin is the same as the helical pitch. We investigate the cause of the pattern by following the traces of selected voxels through the multi-slive detector array as a function of view position. This forms an "extracted sinogram" which represents the data used to reconstruct the specific voxel. Now we can determine the cause of the artifact by correlating the windmill streak in the image with the extracted data. The investigation shows that inadequate sampling along the longitudinal direction causes the artifact.

Method and system for automatically reducing aliasing artifacts

Abstract: Artifacts in an image introduced by sub-Nyquist aliasing are reduced below a visually perceptible level by a method comprising the steps of: providing an input image having sub-Nyquist aliasing artifacts; using a visual perception algorithm to identify the location and characteristics of the sub-Nyquist aliasing artifacts, thereby generating artifact coordinates and parameters; and processing the sub-Nyquist aliasing artifacts by reference to the artifact coordinates and parameters to reduce their visibility, thereby providing an artifact corrected image.

Thoracic aorta at multi-detector row CT: motion artifact with various reconstruction windows.

Abstract: The authors assessed motion artifact of the thoracic aorta in 25 patients who underwent multi–detector row computed tomography (CT) with retrospective electrocardiographic (ECG) gating. CT reconstructions centered at four phases of diastole were compared for five different levels of the thoracic aorta. A significant positive correlation was observed between heart rate and motion artifact (r = 0.72, P < .001). The optimal reconstruction phase varied between patients, and this was directly related to heart rate. For patients with a heart rate of 70 beats per minute, the reconstruction phase centered at 75% of the R-R interval had the significantly least motion artifact (P = .004). Conversely, the optimal reconstruction phase for patients with heart rates above 70 beats per minute was centered at 50% of the R-R interval (P = .09). © RSNA, 2003

Method and apparatus for identifying spectral artifacts

Abstract: The invention provides an apparatus and methods for determining whether spectral data obtained from a region of a tissue sample (402) are affected by an artifact. Artifacts include, for example, lighting artifacts such as glare and shadow and obstruction artifacts, such as blood, a speculum, a smoke tube, or other obstruction. Additionally, the invention provides an apparatus and methods for obtaining redundant spectral data of a given region of a sample (402). A redundant set of spectral data is useful where one or more artifacts affect some but not all sets of the spectral data, such that the redundant set of data is unaffected by the artifact and is representative of the tissue. An embodiment of the invention comprises using representative spectral data in diagnosing a condition of a region of tissue (402).

Magnetic resonance imaging equipment

Abstract: PROBLEM TO BE SOLVED: To achieve the shortening of a photographing time without producing a turnback artifact even if the number of echoes acquired in one block is reduced in relation to a propeller MRI method and to enable high-speed imaging as a whole by enabling high-speed operation by reducing an operation quantity. SOLUTION: The magnetic resonance imaging equipment is constituted so as not only to irradiate the subject placed in a static magnetic field with RF pulses but also to apply a series of inclined magnetic fields to receive an induced nuclear magnetic resonance signal (echo signal) using a multiple RF receiving coil comprising at least two RF receiving coils. Herein, in this magnetic resonance imaging equipment, a parallel MRI method is adapted to an echo signal group acquired by substracting the number of echoes per one block of the propeller MRI method and, after a reconstituted image acquired by removing a turnback artifact is subjected to inverse Forier transform to be turned to the echo signal group on the measuring space corresponding to the block, processing for rearranging this echo signal group to an arbitrarily determined image coordinates system to synthesize the same is performed with respect to the echo signal groups of all blocks to reconstitute a final image using the echo signal group after synthesis in the image coordinates system. COPYRIGHT: (C)2005,JPO&NCIPI

Automated statistical self-calibrating detection and removal of blemishes in digital images based on a dust map developed from actual image data

Abstract: A method of automatically correcting dust artifact regions within images acquired by a system including a digital camera includes digitally-acquiring one or more original images with the digital camera. Probabilities that certain pixels correspond to dust artifact regions within the one or more digitally-acquired images are determined. The dust artifact regions are associated with one or more extracted parameters relating to the optical system when the one or more images were acquired. A statistical dust map is formed including mapped dust regions based on the dust artifact probability determining and associating operations. Pixels corresponding to dust artifact regions within the one or more original images are corrected based on the associated statistical dust map.