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Information Technology in Biomedicine, IEEE Transactions on

Issue 2 • Date March 2007

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Displaying Results 1 - 17 of 17
  • Table of contents

    Page(s): C1 - C4
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  • IEEE Transactions on Information Technology in Biomedicine publication information

    Page(s): C2
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  • Multiclass Support Vector Machines for EEG-Signals Classification

    Page(s): 117 - 126
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (285 KB) |  | HTML iconHTML  

    In this paper, we proposed the multiclass support vector machine (SVM) with the error-correcting output codes for the multiclass electroencephalogram (EEG) signals classification problem. The probabilistic neural network (PNN) and multilayer perceptron neural network were also tested and benchmarked for their performance on the classification of the EEG signals. Decision making was performed in two stages: feature extraction by computing the wavelet coefficients and the Lyapunov exponents and classification using the classifiers trained on the extracted features. The purpose was to determine an optimum classification scheme for this problem and also to infer clues about the extracted features. Our research demonstrated that the wavelet coefficients and the Lyapunov exponents are the features which well represent the EEG signals and the multiclass SVM and PNN trained on these features achieved high classification accuracies View full abstract»

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  • Addressing the Future of Clinical Information Systems—Web-Based Multilayer Visualization

    Page(s): 127 - 140
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (681 KB) |  | HTML iconHTML  

    This paper addresses some key issues relating to the development of new technology for clinical information systems (CIS) in relation to imaging and visualizing data. With the increasing importance of molecular and cellular biology, a new type of medicine, molecular based medicine, is now developing. This will significantly alter the way in which medicine is practiced. The view is presented that CIS will need to operate seamlessly across the Biological Continuum, i.e., the hierarchy of the human organism comprising systems, viscera, tissue, cells, proteins, and genes. We propose a multilayered visualization interface, which operates across the Biological Continuum, based on Web-based technology. A visualization interface package for two-dimensional and three-dimensional image data at the visceral and cellular levels is described. Two application examples are presented: 1) MR knee images, at the visceral level and 2) endothelial nuclei images, acquired from confocal laser microscopy, at the cellular level View full abstract»

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  • SAKURA-Viewer: Intelligent Order History Viewer Based on Two-Viewpoint Architecture

    Page(s): 141 - 152
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (786 KB) |  | HTML iconHTML  

    We propose a new intelligent order history viewer applied to consolidating and visualizing data. SAKURA-viewer is a highly effective tool, as: 1) it visualizes both the semantic viewpoint and the temporal viewpoint of patient records simultaneously; 2) it promotes awareness of contextual information among the daily data; and 3) it implements patient-centric data entry methods. This viewer contributes to decrease the user's workload in an order entry system. This viewer is now incorporated into an order entry system being run on an experimental basis. We describe the evaluation of this system using results of a user satisfaction survey, analysis of information consolidation within the database, and analysis of the frequency of use of data entry methods View full abstract»

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  • Performance Analysis of a Medical Record Exchanges Model

    Page(s): 153 - 160
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (325 KB) |  | HTML iconHTML  

    Electronic medical record exchange among hospitals can provide more information for physician diagnosis and reduce costs from duplicate examinations. In this paper, we proposed and implemented a medical record exchange model. According to our study, exchange interface servers (EISs) are designed for hospitals to manage the information communication through the intra and interhospital networks linked with a medical records database. An index service center can be given responsibility for managing the EIS and publishing the addresses and public keys. The prototype system has been implemented to generate, parse, and transfer the health level seven query messages. Moreover, the system can encrypt and decrypt a message using the public-key encryption algorithm. The queuing theory is applied to evaluate the performance of our proposed model. We estimated the service time for each queue of the CPU, database, and network, and measured the response time and possible bottlenecks of the model. The capacity of the model is estimated to process the medical records of about 4000 patients/h in the 1-MB network backbone environments, which comprises about the 4% of the total outpatients in Taiwan View full abstract»

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  • Real-Time Volume Rendering Visualization of Dual-Modality PET/CT Images With Interactive Fuzzy Thresholding Segmentation

    Page(s): 161 - 169
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (808 KB) |  | HTML iconHTML  

    Three-dimensional (3-D) visualization has become an essential part for imaging applications, including image-guided surgery, radiotherapy planning, and computer-aided diagnosis. In the visualization of dual-modality positron emission tomography and computed tomography (PET/CT), 3-D volume rendering is often limited to rendering of a single image volume and by high computational demand. Furthermore, incorporation of segmentation in volume rendering is usually restricted to visualizing the pre-segmented volumes of interest. In this paper, we investigated the integration of interactive segmentation into real-time volume rendering of dual-modality PET/CT images. We present and validate a fuzzy thresholding segmentation technique based on fuzzy cluster analysis, which allows interactive and real-time optimization of the segmentation results. This technique is then incorporated into a real-time multi-volume rendering of PET/CT images. Our method allows a real-time fusion and interchangeability of segmentation volume with PET or CT volumes, as well as the usual fusion of PET/CT volumes. Volume manipulations such as window level adjustments and lookup table can be applied to individual volumes, which are then fused together in real time as adjustments are made. We demonstrate the benefit of our method in integrating segmentation with volume rendering in its application to PET/CT images. Responsive frame rates are achieved by utilizing a texture-based volume rendering algorithm and the rapid transfer capability of the high-memory bandwidth available in low-cost graphic hardware View full abstract»

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  • Architecture and Performance of a Grid-Enabled Lookup-Based Biomedical Optimization Application: Light Scattering Spectroscopy

    Page(s): 170 - 178
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (379 KB) |  | HTML iconHTML  

    This paper presents a case study of a Grid-enabled implementation of light scattering spectroscopy (LSS). The LSS technique allows noninvasive detection of precancerous changes in human epithelium, differentiating from traditional biopsies by allowing in vivo diagnosis of tissue samples and quantitative analyses of parameters related to cancerous changes via numerical techniques. This paper describes the architecture of GridLSS and its integration with a Web-based Grid computing portal. GridLSS solves an optimization problem of determining the light scattering spectrum that best fits experimental spectral data among a large set of spectra computed analytically using rigorous Mie theory. The novel approach taken in this paper is based on the precomputation and storage of Mie theory spectra in lookup databases that are queried during the minimization process. The paper makes three important contributions: 1) it presents a novel parallel application for LSS analysis that delivers high performance in wide-area distributed computing environment; 2) it evaluates and analyzes the performance of this application in cluster-based high-performance computing environments that are typical of Grid deployments; and 3) it shows that the performance of GridLSS benefits significantly from the use of on-demand Grid data transfers based on virtualized distributed file systems and from user-level caches for remote file system data View full abstract»

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  • Automatic Method to Compare the Lanes in Gel Electrophoresis Images

    Page(s): 179 - 189
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1005 KB) |  | HTML iconHTML  

    Gel electrophoresis (GE) is an important tool in genomic analysis. GE results are presented using images. Each image contains several vertical lanes. Each lane consists of several horizontal bands. Two lanes are identical if the relative positions of the bands are the same. We present a computer method designed to compare the lanes and identify identical lanes. This method, developed using many image-processing techniques, is applied to segment the lanes and bands in GE images. The lanes are then converted into "position vectors" that describe the positions of the bands. Comparing lanes becomes equivalent to comparing the position vectors. This method can accurately identify identical lanes, helping biologists to identify the identical lanes from many lanes with much less effort View full abstract»

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  • Medical Image Categorization and Retrieval for PACS Using the GMM-KL Framework

    Page(s): 190 - 202
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1091 KB) |  | HTML iconHTML  

    This paper presents an image representation and matching framework for image categorization in medical image archives. Categorization enables one to determine automatically, based on the image content, the examined body region and imaging modality. It is a basic step in content-based image retrieval (CBIR) systems, the goal of which is to augment text-based search with visual information analysis. CBIR systems are currently being integrated with picture archiving and communication systems for increasing the overall search capabilities and tools available to radiologists. The proposed methodology is comprised of a continuous and probabilistic image representation scheme using Gaussian mixture modeling (GMM) along with information-theoretic image matching via the Kullback-Leibler (KL) measure. The GMM-KL framework is used for matching and categorizing X-ray images by body regions. A multidimensional feature space is used to represent the image input, including intensity, texture, and spatial information. Unsupervised clustering via the GMM is used to extract coherent regions in feature space that are then used in the matching process. A dominant characteristic of the radiological images is their poor contrast and large intensity variations. This presents a challenge to matching among the images, and is handled via an illumination-invariant representation. The GMM-KL framework is evaluated for image categorization and image retrieval on a dataset of 1500 radiological images. A classification rate of 97.5% was achieved. The classification results compare favorably with reported global and local representation schemes. Precision versus recall curves indicate a strong retrieval result as compared with other state-of-the-art retrieval techniques. Finally, category models are learned and results are presented for comparing images to learned category models View full abstract»

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  • Spatial Modeling and Classification of Corneal Shape

    Page(s): 203 - 212
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (370 KB) |  | HTML iconHTML  

    One of the most promising applications of data mining is in biomedical data used in patient diagnosis. Any method of data analysis intended to support the clinical decision-making process should meet several criteria: it should capture clinically relevant features, be computationally feasible, and provide easily interpretable results. In an initial study, we examined the feasibility of using Zernike polynomials to represent biomedical instrument data in conjunction with a decision tree classifier to distinguish between the diseased and non-diseased eyes. Here, we provide a comprehensive follow-up to that work, examining a second representation, pseudo-Zernike polynomials, to determine whether they provide any increase in classification accuracy. We compare the fidelity of both methods using residual root-mean-square (rms) error and evaluate accuracy using several classifiers: neural networks, C4.5 decision trees, Voting Feature Intervals, and Nainodotumlve Bayes. We also examine the effect of several meta-learning strategies: boosting, bagging, and Random Forests (RFs). We present results comparing accuracy as it relates to dataset and transformation resolution over a larger, more challenging, multi-class dataset. They show that classification accuracy is similar for both data transformations, but differs by classifier. We find that the Zernike polynomials provide better feature representation than the pseudo-Zernikes and that the decision trees yield the best balance of classification accuracy and interpretability View full abstract»

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  • Enhancing IHE XDS for Federated Clinical Affinity Domain Support

    Page(s): 213 - 221
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (314 KB) |  | HTML iconHTML  

    One of the key problems in healthcare informatics is the inability to share patient records across enterprises. To address this problem, an important industry initiative called "integrating the healthcare enterprise (IHE)" specified the "cross enterprise document sharing (XDS)" profile. In the IHE XDS, healthcare enterprises that agree to work together form a "clinical affinity domain" and store healthcare documents in an ebXML registry/repository architecture to facilitate their sharing. The affinity domains also agree on a common set of policies such as coding lists to be used to annotate clinical documents in the registry/repository and the common schemes for patient identification. However, since patients expect their records to follow them as they move from one clinical affinity domain to another, there is a need for affinity domains to be federated to enable information exchange. In this paper, we describe how IHE XDS can be enhanced to support federated clinical affinity domains. We demonstrate that federation of affinity domains are facilitated when ontologies, rather than coding term lists, are used to annotate clinical documents. Furthermore, we describe a patient identification protocol that eliminates the need to keep a master patient index file for the federation View full abstract»

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  • Web-Based Electronic Data Collection System to Support Electrochemotherapy Clinical Trial

    Page(s): 222 - 230
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (496 KB) |  | HTML iconHTML  

    Many branches of the healthcare industry are being influenced by information and communication technology (ICT). Clinical trials are not an exception. Despite this fact, more than 75% of clinical trials data are being collected on paper records. Recent ICT advances, such as broad acceptance of Internet Technology which are rapidly improving electronic data collection (EDC) tools, however, may soon reduce this percentage of "paper" supported clinical trials. In this paper, we present our Web-based EDC system designed to support a small-scale research-oriented clinical trial for establishing standard operating procedures (SOP) for electrochemotherapy with a new medical device, named Cliniporator. The definition of the SOP can only be based on a comprehensive analysis of collected data and results of clinical trial. Therefore, it is necessary to record treatment efficiency and, in this respect, to carefully follow and collect treatment parameters. We thus established central database and the Web application for filling database with data submitted by users from distant medical centers across Europe. Also, we enabled transmitting of data stored on the local Cliniporator medical devices to the central database as well as submitting of tumor images and marking of tumor nodules on interactive human map developed in Macromedia Flash. We provided users with dynamically generated basic statistics, and, several times during data collection process, we performed statistical data analysis. In order to assure high quality of data in a database, we included several mechanisms: automatic data validation, digital signatures, the form completeness notification system, e-mail alerting of completed forms, and "check tables." After 13 months of using the systems, we performed a simple usability evaluation of the system by asking users to answer to a questionnaire, and here we present the results. With this paper, we try to share our experience and encourage others to exploit Internet an- - d Web technologies to improve clinical trials data collection, follow up, and data analysis View full abstract»

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  • Analysis of Telemedicine Diffusion: The Case of China

    Page(s): 231 - 233
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (48 KB) |  | HTML iconHTML  

    Telemedicine helps developing countries deliver medical services to underdeveloped rural areas where health resources are deficient. Yet telemedicine diffusion in the largest developing country, China, remains a secret to the world. This paper examines the evolution of telemedicine in China, analyzes factors influencing the diffusion of telemedicine, and provides recommendations to overcome obstacles to telemedicine View full abstract»

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  • Search for Editor-in-Chief

    Page(s): 234
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  • 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2007)

    Page(s): 235 - 236
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  • IEEE Transactions on Information Technology in Biomedicine Information for authors

    Page(s): C3
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Aims & Scope

The IEEE Transactions on Information Technology in Biomedicine publishes basic and applied papers of information technology applications in health, healthcare and biomedicine.

 

This Transaction ceased publication in 2012. The current retitled publication is IEEE Journal of Biomedical and Health Informatics.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Yuan-ting Zhang
427, Ho Sin Hang Engineering Building, The Chinese
University of Hong Kong, Shatin, NT, Hong Kong
ytzhang@ee.cuhk.edu.hk
Phone:+852 2609-8458
Fax:+852 2609-5558