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Engineering in Medicine and Biology Magazine, IEEE

Issue 2 • Date March-April 2006

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Displaying Results 1 - 25 of 32
  • Spring cleaning and ethics in our backyard

    Publication Year: 2006 , Page(s): 4 - 5
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  • Advertisers' Index

    Publication Year: 2006 , Page(s): 136
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  • Using small numbers of subjects in fMRI-based research

    Publication Year: 2006 , Page(s): 52 - 59
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    This article reviews a number of issues related to the special features and potentials associated with doing functional brain imaging experiments with one or a small number of subjects. It concludes with a speculation that, ironically, it may someday turn out that the information from a few brains, thoroughly studied, will reveal more about universal aspects of human brain function and organization than the current torrent of studies from large collections of brains. View full abstract»

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  • Multivariate statistical analysis in fMRI

    Publication Year: 2006 , Page(s): 60 - 64
    Cited by:  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (285 KB) |  | HTML iconHTML  

    The paper briefly discussed different statistical analysis in functional magnetic resonance imaging (fMRI). Multivariate regression analysis with multiple comparisons corrections allows the determination of activated voxels that can then be grouped into regions of interest (ROIs). Principal component analysis (PCA) is useful in extracting common temporal response features of an ROI as well as differentiating the temporal response of groups of commonly responding ROI. It can also be used to examine differences in the temporal response of subgroups of subjects in the study. Structural equation modeling (SEM) is a technique that requires a priori knowledge of the connections and their direction between ROIs. It is particularly useful in identifying changes in connectivity that result from different interventions or different classes of patients. View full abstract»

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  • Wide open window

    Publication Year: 2006 , Page(s): 22 - 23
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  • Biomedical engineering in the Czech Republic

    Publication Year: 2006 , Page(s): 16 - 19
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  • 2006 EMBS administrative committee

    Publication Year: 2006 , Page(s): 134
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  • The future appears to promise a more integrative approach to functional brain imaging.

    Publication Year: 2006 , Page(s): 26
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  • Exploratory analysis of brain connectivity with ICA

    Publication Year: 2006 , Page(s): 102 - 111
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1072 KB) |  | HTML iconHTML  

    Covariance-based methods of exploration of functional connectivity of the brain from functional magnetic resonance imaging (fMRI) experiments, such as principal component analysis (PCA) and structural equation modeling (SEM), require a priori knowledge such as an anatomical model to infer functional connectivity. In this research, a hybrid method, combining independent component analysis (ICA) and SEM, which is capable of deriving functional connectivity in an exploratory manner without the need of a prior model is introduced. The spatial ICA (SICA) derives independent neural systems or sources involved in task-related brain activation, while an automated method based on the SEM finds the structure of the connectivity among the elements in independent neural systems. Unlike second-order approaches used in earlier studies, the task-related neural systems derived from the ICA provide brain connectivity in the complete statistical sense. The use and efficacy of this approach is illustrated on two fMRI datasets obtained from a visual task and a language reading task. View full abstract»

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  • An analysis of IEEE publications

    Publication Year: 2006 , Page(s): 6 - 9
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (302 KB) |  | HTML iconHTML  

    This study reports on a few elements of the scientific production of the IEEE. Other features could be displayed that would be interesting for a better understanding of the trajectories of the societies, journals, etc. The possibility of projecting new data onto the current spaces allows researchers to see if journals are static (the concepts and methods remaining stable) or dynamic (evolutions, ruptures can be tracked). In other words, this type of analysis can be used as a strategic tool to follow the impact and trends in engineering sciences. The fact that the authors concentrate on the IEEE publications prohibits any comparison with other societies publishing engineering papers. Such insights are feasible through the analysis of the INSPEC database. This could bring other clues on the coverage, the competition, and the reaction to new areas. View full abstract»

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  • Unmixing fMRI with independent component analysis

    Publication Year: 2006 , Page(s): 79 - 90
    Cited by:  Papers (40)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2441 KB) |  | HTML iconHTML  

    Independent component analysis (ICA) is a statistical method used to discover hidden factors (sources or features) from a set of measurements or observed data such that the sources are maximally independent. Typically, it assumes a generative model where observations are assumed to be linear mixtures of independent sources and works with higher-order statistics to achieve independence. ICA has recently demonstrated considerable promise in characterizing functional magnetic resonance imaging (fMRI) data, primarily due to its intuitive nature and ability for flexible characterization of the brain function. In this article, ICA is introduced and its application to fMRI data analysis is reviewed. View full abstract»

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  • Providing senior design students with a clinical perspective

    Publication Year: 2006 , Page(s): 20 - 21
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (161 KB)  

    This article aims to provide students with a clinical perspective of medical device design. This study shows that it is not only important for students to understand how medical devices are designed and function but how these devices are used by patients, physicians, surgeons, nurses, and physical therapists too. For implantable devices, this includes problems associated with the preparation, insertion, and removal of devices in a patient's body. For monitoring or imaging equipment, this includes problems associated with device set up and operation and interpretation of data. This knowledge is important to medical device designers who may be able to avoid or solve many of these problems through good design. View full abstract»

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  • Behind the scenes at EMBC '05

    Publication Year: 2006 , Page(s): 124 - 131
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  • A brief introduction to functional MRI

    Publication Year: 2006 , Page(s): 24 - 26
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (519 KB) |  | HTML iconHTML  

    IEEE Engineering in Medicine and Biology Magazine focuses on modern methods for the analysis of data from functional magnetic resonance imaging (fMRI) studies. Accordingly, the guest editors have seen fit to begin with a brief article on the history, mechanisms and methods behind fMRI. This is followed by the presentation of recent significant progress in paradigm design for fMRI as well as development of other methods for assessing the functional anatomy of the human brain, such as diffusion tensor imaging, for mapping white matter fiber tracts. Thus, the future appears to promise a more integrative approach to functional brain imaging, in which data from multiple modalities are entered into comprehensive analyses of brain function and connectivity. View full abstract»

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  • IEEE Engineering in Medicine and Biology Magazine - Vol 25 No. 2

    Publication Year: 2006 , Page(s): 0_1
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    Freely Available from IEEE
  • Table of contents

    Publication Year: 2006 , Page(s): 1 - 2
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    Freely Available from IEEE
  • New to the society news

    Publication Year: 2006 , Page(s): 10 - 11
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  • Hello from your new representative!

    Publication Year: 2006 , Page(s): 12 - 13
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  • Book reviews

    Publication Year: 2006 , Page(s): 14 - 15
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  • First Call for Papers Announcement

    Publication Year: 2006 , Page(s): 17 - 18
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    Freely Available from IEEE
  • Evaluating fMRI preprocessing pipelines

    Publication Year: 2006 , Page(s): 27 - 41
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (576 KB) |  | HTML iconHTML  

    This article reviews the evaluation and optimization of the preprocessing steps for blood-oxygenation-level-dependent (BOLD) functional magnetic resonance imaging (fMRI). This technique indirectly measures changes in local neuronal firing rates by measuring associated changes in deoxy-hemoglobin concentrations in nearby blood vessels. Based on the existing literature, it is impossible to make conclusive statements about the optimal algorithm and software implementations for any single preprocessing step, let alone entire pipelines. The author believes that the present focus on the technological testing of preprocessing steps should be balanced by approaches that test the pipeline. This should include all interactions measured using metrics that are closely linked to research and diagnostic questions addressed at the end of the processing pipeline. The goal is to avoid single expedient or default pipelines by developing a framework capable of potentially testing thousands of possible pipeline implementations per dataset. To achieve this goal, researchers depend on recent developments in software tools for managing neuroimaging workflows. View full abstract»

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  • Modeling and inference of multisubject fMRI data

    Publication Year: 2006 , Page(s): 42 - 51
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (409 KB) |  | HTML iconHTML  

    This article reviews four commonly used approaches to group modeling in fMRI. The methods differ in their computational intensity (FSL with its two-level estimation including MCM being the most intense) and assumptions (SPM2 with its assumption of spatially homogeneous covariance Vg being most restrictive). This study also distinguishes fixed-effects models from mixed-effects models and motivates the importance of a mixed-effects model for group fMRI analysis. The sections following that describe single-subject modeling and show a general method for estimating the group model. View full abstract»

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  • Surfing the brain

    Publication Year: 2006 , Page(s): 65 - 78
    Cited by:  Papers (2)
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    In this paper, an overview with unification of techniques that deploy the wavelet transform in the spatial domain for the analysis of functional magnetic resonance imaging (fMRI) is presented. View full abstract»

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  • Increasing the effect size in event-related fMRI studies

    Publication Year: 2006 , Page(s): 91 - 101
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1989 KB) |  | HTML iconHTML  

    Independent component analysis (ICA) has proved to be a powerful method for exploratory analysis of functional magnetic resonance imaging (fMRI) data. It has been used to uncover unexpected activations in fMRI data derived from brain activation. ICA has been used to characterize other sources of variability in the fMRI signal besides task-related activity, as well as challenging some of the assumptions inherent in other fMRI analysis methods. As a data-driven fMRI analysis technique, the philosophy of ICA is often in disagreement with hypothesis-driven methods. By exploiting the fact that much of fMRI data has deterministic spatial-temporal structure, a scheme employing ICA denoising and least squares (LS) estimation of the evoked hemodynamic response (HDR) is proposed. Simulations suggest that the method is more robust to different noise models compared to naive application of LS. The result is a considerably increased level of significance of activation for a given voxel but still qualitatively similar spatial distribution of activations over all voxels. This suggests that the proposed method has the potential to substantially reduce total scanning time requirements to achieve the same level of statistically significant activation. View full abstract»

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  • fMRI neuroinformatics

    Publication Year: 2006 , Page(s): 112 - 119
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1743 KB) |  | HTML iconHTML  

    Functional magnetic resonance imaging (fMRI) generates vast amounts of data. The handling, processing, and analysis of fMRI data would be inconceivable without computer-based methods. fMRI neuroinformatics is concerned with research, development, and operation of these methods. Reconstruction, rudimentary analysis, and visualization tools are implemented in software controlling modern MRI scanners. Research in advanced methods for analysis of subtle activation patterns, realistic physiological modeling, or integration of data from multiple subjects is the basis for a lively research field and has led to the development of a large number of tools. View full abstract»

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Aims & Scope

IEEE Engineering in Medicine and Biology Magazine contains articles on current technologies and methods used in biomedical and clinical engineering.

 

This Magazine ceased publication in 2010. The current retitled publication is IEEE Pulse.

Full Aims & Scope