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IEEE Signal Processing Magazine

Issue 4 • Date July 2010

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Displaying Results 1 - 23 of 23
  • [Front cover]

    Publication Year: 2010, Page(s): C1
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  • Table of contents

    Publication Year: 2010, Page(s): 1
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  • [IEEE Signal Processing Magazine Staff Listing]

    Publication Year: 2010, Page(s): 2
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  • Socializing Digital Signal Processing [From the Editor]

    Publication Year: 2010, Page(s):2 - 119
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  • March Madness - The Good Kind [President's Message]

    Publication Year: 2010, Page(s): 4
    Cited by:  Papers (1)
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  • DSPs See Gains in Their Impact on New Medical Imaging Designs [Special Reports]

    Publication Year: 2010, Page(s):6 - 134
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (151 KB) | HTML iconHTML

    Digital signal processing (DSP) is having a major impact on advancing the state of the art of medical imaging. The advantages of DSP are well established: They operate in real time, they're highly reliable, and they are very energy efficient. They're also relatively inexpensive. But the medical imaging market continues to push for more technical innovation. That's putting more focus on higher imag... View full abstract»

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  • The Roles of Signal Processing in Medical Imaging [From the Guest Editors]

    Publication Year: 2010, Page(s):12 - 140
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  • Three-Dimensional Tissue Deformation Recovery and Tracking

    Publication Year: 2010, Page(s):14 - 24
    Cited by:  Papers (13)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3100 KB) | HTML iconHTML

    Recent advances in surgical robotics have provided a platform for extending the current capabilities of minimally invasive surgery by incorporating both preoperative and intraoperative imaging data. In this tutorial article, we introduce techniques for in vivo three-dimensional (3-D) tissue deformation recovery and tracking based on laparoscopic or endoscopic images. These optically based techniqu... View full abstract»

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  • Machine Learning in Medical Imaging

    Publication Year: 2010, Page(s):25 - 38
    Cited by:  Papers (10)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3010 KB) | HTML iconHTML

    This article will discuss very different ways of using machine learning that may be less familiar, and we will demonstrate through examples the role of these concepts in medical imaging. Although the term machine learning is relatively recent, the ideas of machine learning have been applied to medical imaging for decades, perhaps most notably in the areas of computer-aided diagnosis (CAD) and func... View full abstract»

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  • Canonical Correlation Analysis for Data Fusion and Group Inferences

    Publication Year: 2010, Page(s):39 - 50
    Cited by:  Papers (63)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3081 KB) | HTML iconHTML

    We have presented two CCA-based approaches for data fusion and group analysis of biomedical imaging data and demonstrated their utility on fMRI, sMRI, and EEG data. The results show that CCA and M-CCA are powerful tools that naturally allow the analysis of multiple data sets. The data fusion and group analysis methods presented are completely data driven, and use simple linear mixing models to dec... View full abstract»

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  • Digital Topology in Brain Imaging

    Publication Year: 2010, Page(s):51 - 59
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3041 KB) | HTML iconHTML

    Modeling topology in medical image processing algorithms has emerged as a powerful technique for computing structural representations that are consistent with the underlying anatomy. When applied to high resolution images of the brain, these methods have proven to be extremely beneficial to neuroscientific studies in generating mathematical representations of the cerebral cortex and other brain st... View full abstract»

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  • Tomographic Reconstruction in the 21st Century

    Publication Year: 2010, Page(s):60 - 80
    Cited by:  Papers (13)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2845 KB) | HTML iconHTML

    Image reconstruction from projections is the field that lays the foundations for computed tomography (CT). For several decades, the established principles were applied not only to medical scanners in radiology and nuclear medicine but also to industrial scanning. When speaking of image reconstruction from projections, one is generally considering the problem of recovering some density function fro... View full abstract»

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  • Model-Based Image Reconstruction for MRI

    Publication Year: 2010, Page(s):81 - 89
    Cited by:  Papers (40)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (945 KB) | HTML iconHTML Multimedia Media

    Magnetic resonance imaging (MRI) is a sophisticated and versatile medical imaging modality. The inverse FFT has served the MR community very well as the conventional image reconstruction method for k-space data with full Cartesian sampling. And for well sampled non-Cartesian data, the gridding method with appropriate density compensation factors is fast and effective. But when only under-sampled d... View full abstract»

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  • Parallel MRI Using Phased Array Coils

    Publication Year: 2010, Page(s):90 - 98
    Cited by:  Papers (26)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2384 KB) | HTML iconHTML

    Parallel MRI using phased array coils can be viewed as an application of the multichannel sampling theory. Specifically, in the case of uniform 1-D undersampling, Papoulis' classical reconstruction formulas correspond well to the existing parallel MRI reconstruction algorithms, and a number of practical issues can be analyzed in this context. However, parallel MRI also presents several unique sign... View full abstract»

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  • Probing Waveform Synthesis and Receiver Filter Design

    Publication Year: 2010, Page(s):99 - 112
    Cited by:  Papers (14)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2190 KB) | HTML iconHTML

    Probing waveform synthesis and receive filter design play crucial roles in achievable performance for many active sensing applications, including radar, sonar, medical imaging, and communications (channel estimation and spread spectrum). A flexible receive filter design approach can be used to compensate for missing features of the probing waveforms, at the costs of lower signal-to-noise ratio (SN... View full abstract»

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  • Nonrigid Registration of Medical Images: Theory, Methods, and Applications [Applications Corner]

    Publication Year: 2010, Page(s):113 - 119
    Cited by:  Papers (30)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1230 KB) | HTML iconHTML

    Medical image registration plays an increasingly important role in many clinical applications, including the detection and diagnosis of diseases, planning of therapy, guidance of interventions, and the follow-up and monitoring of patients. The primary goal of image registration is to find corresponding anatomical or functional locations in two or more images. This has many applications: registrati... View full abstract»

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  • Improving FIR Filter Coefficient Precision [DSP Tips & Tricks]

    Publication Year: 2010, Page(s):120 - 124
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (401 KB) | HTML iconHTML

    There is a method for increasing the precision of fixed-point coefficients used in linear-phase finite impulse response (FIR) filters to achieve improved filter performance. The improved performance is accomplished without increasing either the number of coefficients or coefficient bitwidths. At first thought, such a process does not seem possible, but this article shows exactly how this novel fil... View full abstract»

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  • Compression of Medical Sensor Data [Exploratory DSP]

    Publication Year: 2010, Page(s):125 - 130
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (878 KB) | HTML iconHTML

    Over the course of the last 20 years, compression has evolved from a somewhat esoteric domain of mathematics and computer science into a ubiquitous consumer electronics technology. Given the prevalence and success of speech, audio, image, and video compression algorithms in consumer electronics, it is surprising that many high-speed digital signal processing (DSP) systems such as wireless infrastr... View full abstract»

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  • Human Brain Connectomics: Networks, Techniques, and Applications [Life Sciences]

    Publication Year: 2010, Page(s):131 - 134
    Cited by:  Papers (10)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1262 KB) | HTML iconHTML

    The human brain is organized into a collection of interacting networks with specialized functions to support various cognitive functions. The word "connectome" first burst on the scene with the work of Sporns et al., who urged brain researchers to advance a comprehensive structural description of the elements and connections forming the human brain. An increasing body of evidence indicates that sc... View full abstract»

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  • Perceptual Quality Measurement—Towards a More Efficient Process for Validating Objective Models [Standards in a Nutshell]

    Publication Year: 2010, Page(s):136 - 140
    Cited by:  Papers (7)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (157 KB) | HTML iconHTML

    The Quality of Service Metrics (QoSM) Committee of the Alliance for Telecommunication Industry Standards (ATIS) Internet Protocol Television (IPTV) Interoperability Forum (ΠF) is tasked with defining how objective quality metrics can provide meaningful IPTV performance measures. This group has reviewed current objective quality models as well as the processes by which such models are valida... View full abstract»

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  • Techware: www.sspnet.eu: A Web Portal for Social Signal Processing [Best of the Web]

    Publication Year: 2010, Page(s):142 - 144
    Cited by:  Papers (1)
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  • Dates Ahead

    Publication Year: 2010, Page(s): 146
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  • Brain-Computer Interfacing [In the Spotlight]

    Publication Year: 2010, Page(s):152 - 150
    Cited by:  Papers (11)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1242 KB) | HTML iconHTML

    Recently, CNN reported on the future of brain-computer interfaces (BCIs). BCIs are devices that process a user's brain signals to allow direct communication and interaction with the environment. BCIs bypass the normal neuromuscular output pathways and rely on digital signal processing and machine learning to translate brain signals to action (Figure 1). Historically, BCIs were developed with biome... View full abstract»

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Aims & Scope

IEEE Signal Processing Magazine publishes tutorial-style articles on signal processing research and applications, as well as columns and forums on issues of interest. Its coverage ranges from fundamental principles to practical implementation, reflecting the multidimensional facets of interests and concerns of the community. Its mission is to bring up-to-date, emerging and active technical developments, issues, and events to the research, educational, and professional communities. It is also the main Society communication platform addressing important issues concerning all members.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Min Wu
University of Maryland, College Park
United States 

http://www/ece.umd.edu/~minwu/