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Comparison of fMRI motion correction software tools

NEUROimage 2005年第3期28卷 529-543页

作者： Oakes, TR Johnstone, T Walsh, KSO Greischar, LL Alexander, AL Fox, AS Davidson, RJ Univ Wisconsin Waisman Lab Brain Imaging Madison WI 53705 USA

Motion correction of fMRI data is a widely used step prior to data analysis. In this study, a comparison of the motion correction tools provided by several leading fMRI analysis software packages was performed, including AFNI, AIR, BrainVoyager, FSL, and SPM2. Comparisons were performed using data from typical human studies as well as phantom data. The identical reconstruction, preprocessing, and analysis steps were used on every data set, except that motion correction was performed using various configurations from each soft-ware package. Each package was studied using default parameters, as well as parameters optimized for speed and accuracy. Forty subjects performed a Go/No-go task (an event-related design that investigates inhibitory motor response) and an N-back task (a block-design paradigm investigating working memory). The human data were analyzed by extracting a set of general linear model (GLM)-derived activation results and comparing the effect of motion correction on thresholded activation cluster size and maximum I value. In addition, a series of simulated phantom data sets were created with known activation locations, magnitudes, and realistic motion. Results from the phantom data indicate that AFNI and SPM2 yield the most accurate motion estimation parameters, while AFNI's interpolation algorithm introduces the least smoothing. AFNI is also the fastest of the packages tested. However, these advantages did not produce noticeably better activation results in motion-corrected data from typical human fMRI experiments. Although differences in performance between packages were apparent in the human data, no single software package produced dramatically better results than the others. The "accurate" parameters showed virtually no improvement in cluster t values compared to the standard parameters. While the "fast" parameters did not result in a substantial increase in speed, they did not degrade the cluster results very much either. The phantom and human dat

关键词： Algorithms Artifacts Brain/physiology computer Simulation Humans image processing, computer-assisted/statistics & numerical data Linear Models Magnetic Resonance Imaging/statistics & numerical data Memory, Short-Term/physiology Models, Neurological Movement Oxygen/blood Software

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Conjunction revisited

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NEUROimage 2005年第3期25卷 661-667页

作者： Friston, KJ Penny, WD Glaser, DE Univ Coll Dublin Wellcome Dept Imaging Neurosci London WC1N 3AR England Univ Coll Dublin Inst Cognit Neurosci London WC1N 3AR England

The aim of this note is to revisit the analysis of conjunctions in imaging data. We review some conceptual issues that have emerged from recent discussion (Nichols, T., Brett, M., Andersson, J., Wager, T., Poline, J.-B., this issue. Valid Conjunction Inference with the Minimum Statistic.) and reformulate the conjunction of null hypotheses as a conjunction of k or more effects. Analyses based on minimum statistics have typically used the null hypothesis that k = 0. This enables inferences about one or more effects (k > 0). However, this does not provide control over false-positive rates (FPR) for inferences about a conjunction of k = n effects, over n tests. This is the key point made by Nichols et al., who suggest a procedure based on supremum P values that provides an upper bound on FPR for k = n. Although valid, this is a very conservative procedure, particularly in the context of multiple comparisons. We suggest that an inference on a conjunction of k = n effects is generally unnecessary and distinguish between congruent contrasts that test for the same treatment and incongruent contrasts of the sort used in cognitive conjunctions. For congruent contrasts, the usual inference, k > 0, is sufficient. With incongruent contrasts it is sufficient to infer a conjunction of k > u effects, where u is the number of contrasts that share some uninteresting effect. The issues highlighted by Nichols et al., have important implications for the design and analysis of cognitive conjunction studies and have motivated a change to the SPM software, that affords a test for the more general hypothesis k > u. This more general conjunction test is described. (c) 2005 Elsevier Inc. All rights reserved.

关键词： Arousal/physiology Attention/physiology Bias (Epidemiology) Brain/physiology Humans image Enhancement image processing, computer-assisted/statistics & numerical data Logic Magnetic Resonance Imaging/statistics & numerical data Mathematical Computing Predictive Value of Tests Reproducibility of Results Sensitivity and Specificity

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An improved theoretical P value for SPMs based on discrete local maxima

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NEUROimage 2005年第4期28卷 1056-1062页

作者： Worsley, KJ McGill Univ Dept Math & Stat Montreal PQ H3A 2K6 Canada Montreal Neurol Inst McConnell Brain Imaging Ctr Montreal PQ H3A 2B4 Canada

We present a new continuity correction to the P value for local maxima of a statistical parametric map that bridges the gap between small FWHM, when the Bonferroni correction is accurate, and large FWHM, when random field theory is accurate. The new method, based on discrete local maxima, is always an upper bound (like the Bonferroni), but lower and hence more accurate for large FWHM, without increasing false positives. It resulted in P values that were similar to 43% lower than the best of Bonferroni or random field theory methods when applied to a typical fMRI data set. (c) 2005 Elsevier Inc. All rights reserved.

关键词： Algorithms Brain Mapping/methods Brain Mapping/methods computer Simulation Humans image processing, computer-assisted/statistics & numerical data Magnetic Resonance Imaging Models, Statistical Neural Pathways/physiology Normal Distribution

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Statistical tests for fMRI based on experimental randomization

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NEUROimage 2003年第2期19卷 226-232页

作者： Raz, J Zheng, H Ombao, H Turetsky, B Harvard Univ Sch Med Dept Hlth Care Policy Boston MA 02115 USA Univ Penn Div Biostat Philadelphia PA 19104 USA Univ Illinois Dept Stat Urbana IL USA Univ Penn Brain Behav Lab Philadelphia PA 19104 USA

Statistical parametric mapping (SPM) analysis of fMRI data requires specifying correctly the temporal and spatial noise covariance structure. This is a difficult if not impossible task. When these assumptions are not satisfied, statistical inference can be invalid or inefficient. Permutation tests are free of strong assumptions on the distribution of signal noise. We propose permutation tests of fMRI data based on experimental randomization of the stimulus sequences. Smooth hemodynamic response curves are estimated using quadratic B-splines. We study fMRI data obtained from event-related potential (ERP) oddball paradigm. Tests of two-tone and three-tone stimulus sequences are conducted to illustrate the application of the proposed method. Comparisons of the SPM and proposed method show that a permutation test is more specific and less susceptible to artifacts. (C) 2003 Elsevier Science (USA). All rights reserved.

关键词： Arousal/physiology Artifacts Brain Mapping Brain Mapping Cerebral Cortex/physiology Event-Related Potentials, P300/physiology Humans image processing, computer-assisted/statistics & numerical data Imaging, Three-Dimensional/statistics & numerical data Linear Models Magnetic Resonance Imaging/statistics & numerical data Mathematical Computing Pitch Perception/physiology Psychomotor Performance/physiology Random Allocation

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Functional magnetic resonance imaging (fMRI) "brain reading": detecting and classifying distributed patterns of fMRI activity in human visual cortex

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NEUROimage 2003年第2期19卷 261-270页

作者： Cox, DD Savoy, RL Rowland Inst Sci Inc Cambridge MA 02142 USA Athinoula A Martinos Ctr Struct & Funct Biomed Im Charlestown MA 02129 USA HyperVis Inc Lexington MA 02420 USA

Traditional (univariate) analysis of functional MRI (fMRI) data relies exclusively on the information contained in the time course of individual voxels. Multivariate analyses can take advantage of the information contained in activity patterns across space, from multiple voxels. Such analyses have the potential to greatly expand the amount of information extracted from fMRI data sets. In the present study, multivariate statistical pattern recognition methods, including linear discriminant analysis and support vector machines, were used to classify patterns of fMRI activation evoked by the visual presentation of various categories of objects. Classifiers were trained using data from voxels in predefined regions of interest during a subset of trials for each subject individually. Classification of subsequently collected fMRI data was attempted according to the similarity of activation patterns to prior training examples. Classification was done using only small amounts of data (20 s worth) at a time, so such a technique could, in principle, be used to extract information about a subject's percept on a near real-time basis. Classifiers trained on data acquired during one session were equally accurate in classifying data collected within the same session and across sessions separated by more than a week, in the same subject. Although the highest classification accuracies were obtained using patterns of activity including lower visual areas as input, classification accuracies well above chance were achieved using regions of interest restricted to higher-order object-selective visual areas. In contrast to typical fMRI data analysis, in which hours of data across many subjects are averaged to reveal slight differences in activation, the use of pattern recognition methods allows a subtle 10-way discrimination to be performed on an essentially trial-by-trial basis within individuals, demonstrating that fMRI data contain far more information than is typically appreciated. (C)

关键词： Adult Brain Mapping/methods Brain Mapping/methods Discrimination Learning/physiology Female Humans image processing, computer-assisted/statistics & numerical data Magnetic Resonance Imaging/statistics & numerical data Male Mathematical Computing Middle Aged Multivariate Analysis Pattern Recognition, Visual/physiology Regional Blood Flow/physiology Sensitivity and Specificity Visual Cortex/blood supply Visual Cortex/physiology

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A model-based method for retrospective correction of geometric distortions in diffusion-weighted EPI

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NEUROimage 2002年第1期16卷 177-199页

作者： Andersson, JLR Skare, S Karolinska MR Res Ctr S-17176 Stockholm Sweden

The self-diffusion tensor may be calculated from several echo-planar image acquisitions preceded by different diffusion gradients. Unfortunately, these diffusion gradients cause geometric distortion that must be corrected before estimation of the tensor. In the present paper we suggest and implement a method for retrospective correction of these distortions firmly based on a physical model for the diffusion-weighted images. This method simultaneously estimates subject movement and distortion parameters by finding the set of parameters that minimizes residual error when fitting data to the diffusion tensor model. We show how this notion can be formalized as a quadratic form thereby facilitating the implementation of a rapid algorithm. In addition, we suggest models for how distortions vary with slice position and gradient direction that allow us to substantially reduce the dimensionality of the parameter space. Our results indicate that we are able to estimate both eddy current-induced distortion and subject movement directly from the data without need of any additional measurements. (C) 2002 Elsevier Science (USA).

关键词： Algorithms Artifacts Echo-Planar Imaging/statistics & numerical data Head Movements Humans image processing, computer-assisted/statistics & numerical data Magnetic Resonance Imaging Models, Statistical

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Improved parametric image generation using spatial-temporal analysis of dynamic PET studies

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NEUROimage 2002年第3期15卷 697-707页

作者： Zhou, Y Huang, SC Bergsneider, M Wong, DF Univ Calif Los Angeles Sch Med Dept Mol & Med Pharmacol Los Angeles CA 90095 USA Univ Calif Los Angeles Sch Med Div Neurosurg Los Angeles CA 90095 USA Univ Calif Los Angeles Sch Med Brain Injury ReS Ctr Los Angeles CA 90095 USA Johns Hopkins Med Inst Russell H Morgan Dept Radiol & Radiol Sci Baltimore MD 21287 USA

The value of parametric images that represent both spatial distribution and quantification of the physiological parameters of tracer kinetics has long been recognized. However, the inherent high noise level of pixel kinetics of dynamic PET makes it unsuitable to generate parametric images of the microparameters of tracer kinetic model by conventional weighted nonlinear least squares (WNLS) fitting. Based on the concept that both spatial and temporal information should be integrated to improve parametric image quality, a nonlinear ridge regression with spatial constraint (NLRRSC) parametric imaging algorithm was proposed in this study. For NLRRSC, a term that penalizes local spatial constraint were estimated by component representation model (CRM) with cluster analysis. A hierarchical cluster with average linkage method was used to extract components. The ridge parameter was determined by linear ridge regression theory at each iteration, and a modified Gauss-Newton algorithm was used for minimizing the cost function. Results from a computer simulation showed that the percent mean square error of estimates obtained by NLRRSC can be decreased by 60-80% compared to that of WNLS. The parametric images estimated by NLRRSC are significantly better than the ones generated by WNLS. A highly correlated linear relationship was found between the ROI values calculated from the microparametric images generated by NLRRSC and estimates from ROI kinetic fitting. NLRRSC provided a reliable estimates of glucose metabolite uptake rate with a comparable image quality compared to Patlak analysis. In conclusion, NLRRSC is a reliable and robust parametric imaging algorithm for dynamic PET studies. (C) 2002 Elsevier Science (USA)

关键词： Algorithms Blood Glucose/metabolism Brain/physiology Brain/radionuclide imaging Cluster Analysis computer Simulation Fluorodeoxyglucose F18/diagnostic use Humans image processing, computer-assisted/statistics & numerical data Mathematical Computing Nonlinear Dynamics statistics, Nonparametric Tomography, Emission-Computed/statistics & numerical data

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Sexual dimorphism in the corpus callosum: A characterization of local size variations and a classification driven approach to morphometry

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NEUROimage 2002年第3期17卷 1504-1511页

作者： Pettey, DJ Gee, JC Univ Penn GRASP Lab Dept Comp & Informat Sci Philadelphia PA 19104 USA Univ Penn Dept Radiol Philadelphia PA 19104 USA

We present two complementary quantitative approaches to the problem of characterizing morphometric variations between two distinct populations. The case presented focuses solely on local size variations, but the general method can easily be applied to other scalar morphometric quantities. The first method uses a statistical parametric map (SPM) to ascertain a P value, which indicates whether any statistically significant differences exist between the populations. The second method focuses on finding the best single measurement which can be used for classifying the two populations. For our case study midsagittal cross sections of the corpora callosa from a population of normal males and females are nonrigidly registered (spatially normalized) to an atlas. The resulting deformations are then used to ascertain (i) whether there are any statistically significant differences between the populations and (ii) whether these differences allow one to perform classification. We make use of the Jacobian of the deformation field and normalize it to account for overall volume changes allowing us to focus on differences which are more related to morphometry than scale. From the (SPM) approach to the problem we find evidence of statistically significant differences in the morphology between the populations. Using a linear discriminant function we find that these differences do not appear to be useful for classification. Thus, this dataset provides an example of how statistically significant effects may not be of much diagnostic value. They may be of interest to the research community, but of little value to the clinician. (C) 2002 Elsevier Science (USA).

关键词： Adult Algorithms Analysis of Variance Cluster Analysis Corpus Callosum/anatomy & histology Female Humans image processing, computer-assisted/statistics & numerical data Magnetic Resonance Imaging/statistics & numerical data Male Mathematical Computing Reference Values Sex Characteristics

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Automatic analysis of agarose gel images

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BIOINFORMATICS 2001年第11期17卷 1084-1090页

作者： Adiga, PSU Bhomra, A Turri, MG Nicod, A Datta, SR Jeavons, P Mott, R Flint, J Univ Oxford Wellcome Trust Ctr Human Genet Psychiat Genet Grp Oxford OX3 7BN England Univ Oxford Comp Lab Oxford OX1 3QD England

Motivation: Automatic tools to speed up routine biological processes are very much sought after in bio-medical research. Much repetitive work in molecular biology, such as allele calling in genetic analysis, can be made semiautomatic or task specific automatic by using existing techniques from computer science and signal processing. computerized analysis is reproducible and avoids various forms of human error. Semi-automatic techniques with an interactive check on the results speed up the analysis and reduce the error. Results: We have successfully implemented an image processing software package to automatically analyze agarose gel images of polymorphic DNA markers. We have obtained up to 90% accuracy for the classification of alleles in good quality images and up to 70% accuracy in average quality images. These results are obtained within a few seconds. Even after subsequent interactive checking to increase the accuracy of allele classification to 100%, the overall speed with which the data can be processed is greatly increased, compared to manual allele classification.

关键词： Animals Computational Biology DNA/genetics DNA/isolation & purification Electrophoresis, Agar Gel/statistics & numerical data Genetic Markers image processing, computer-assisted/statistics & numerical data Polymorphism, Genetic Sequence Analysis, DNA/statistics & numerical data Software Software Design

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BioLayout - an automatic graph layout algorithm for similarity visualization

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BIOINFORMATICS 2001年第9期17卷 853-854页

作者： Enright, AJ Ouzounis, CA European Bioinformat Inst Res Programme Computat Genom Grp EMBL Cambridge Outstn Cambridge CB10 1SD England

Graph layout is extensively used in the field of mathematics and computer science, however these ideas and methods have not been extended in a general fashion to the construction of graphs for biological data. To this end, we have implemented a version of the Fruchterman Rheingold graph layout algorithm, extensively modified for the purpose of similarity analysis in biology. This algorithm rapidly and effectively generates clear two (2D) or three-dimensional (3D) graphs representing similarity relationships such as protein sequence similarity. The implementation of the algorithm is general and applicable to most types of similarity information for biological data.

关键词： Algorithms Amino Acid Sequence computer Graphics/statistics & numerical data computer Graphics/trends databases, Protein/statistics & numerical data databases, Protein/statistics & numerical data databases, Protein/trends databases, Protein/trends image processing, computer-assisted/statistics & numerical data image processing, computer-assisted/trends Imaging, Three-Dimensional/statistics & numerical data Imaging, Three-Dimensional/trends Software/statistics & numerical data Software/trends

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