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Biomedical and Health Informatics, IEEE Journal of

Issue 4 • Date July 2013

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Displaying Results 1 - 22 of 22
  • [Front cover]

    Publication Year: 2013 , Page(s): C1
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  • IEEE Journal of Biomedical and Health Informatics publication information

    Publication Year: 2013 , Page(s): C2
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  • Guest Editorial: Terahertz imaging and spectroscopy for biology and biomedicine

    Publication Year: 2013 , Page(s): 765 - 767
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  • Terahertz Spectra of Biotin Based on First Principle, Molecular Mechanical, and Hybrid Simulations

    Publication Year: 2013 , Page(s): 768 - 773
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (587 KB) |  | HTML iconHTML  

    Terahertz (THz) absorption of biotin was simulated using the first principle and the density functional theory (DFT) both in the harmonic approximation and with corrections for the anharmonicity. Anharmonicity corrections were calculated using two different approaches. First, the perturbation theory-based first principle calculations were performed to include third- and fourth-order anharmonicity corrections in atomic displacements to harmonic vibrational states. Second, the atom-centered density matrix propagation molecular dynamics model that provides a good energy conservation was used to calculate the atomic trajectories, velocities, and a dipole moment time history of biotin at low and room temperatures. Predicted low-THz lines agree well with the experimental spectra. The influence of the polyethylene (PE) matrix embedment on the THz spectra of biotin at the nanoscale was studied using the developed hybrid DFT/molecular mechanical approach. While PE is almost transparent at THz frequencies, additional low-THz lines are predicted in the biotin/PE system, which reflects a dynamic interaction between biotin and a surrounding PE cavity. View full abstract»

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  • Terahertz Time-Domain Spectroscopy of Human Blood

    Publication Year: 2013 , Page(s): 774 - 778
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (379 KB) |  | HTML iconHTML  

    In the continuing development of terahertz technology to enable the determination of tissue pathologies in real-time during surgical procedures, it is important to distinguish the measured terahertz signal from biomaterials and fluids, such as blood, which may mask the signal from tissues of interest. In this paper, we present the frequency-dependent absorption coefficients, refractive indices, and Debye relaxation times of whole blood, red blood cells, plasma, and a thrombus. View full abstract»

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  • Temperature-Dependent Terahertz Imaging of Excised Oral Malignant Melanoma

    Publication Year: 2013 , Page(s): 779 - 784
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (556 KB) |  | HTML iconHTML  

    We imaged a single case of oral malignant melanoma using terahertz (THz) reflection imaging at room temperature (20 °C) and below freezing (-20 °C). A malignant nodule beneath the oral tissue surface was visualized using 2-D and B-scan THz imaging techniques. The THz images were well correlated with the histological findings. The nodule was found to have lower water content than that of normal cells, and this water effect may have influenced the THz refractive index and absorption coefficient at 20 °C. The THz spectroscopic image of the frozen tissue at -20 °C showed better contrast because of the lack of liquid water; this implies that there are significant structural differences between malignant oral melanoma cells and normal mucosal cells. The better contrast in the frozen tissue images was due to the greater penetration of THz radiation into the sample. This temperature-dependent THz imaging approach demonstrated the feasibility of accurate imaging of the oral tumor tissue. View full abstract»

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  • Development and Testing of a Single Frequency Terahertz Imaging System for Breast Cancer Detection

    Publication Year: 2013 , Page(s): 785 - 797
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1800 KB) |  | HTML iconHTML  

    The ability to discern malignant from benign tissue in excised human breast specimens in Breast Conservation Surgery (BCS) was evaluated using single frequency terahertz radiation. Terahertz (THz) images of the specimens in reflection mode were obtained by employing a gas laser source and mechanical scanning. The images were correlated with optical histological micrographs of the same specimens, and a mean discrimination of 73% was found for five out of six samples using Receiver Operating Characteristic (ROC) analysis. The system design and characterization is discussed in detail. The initial results are encouraging but further development of the technology and clinical evaluation is needed to evaluate its feasibility in the clinical environment. View full abstract»

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  • Observation of Hydrofluoric Acid Burns on Osseous Tissues by Means of Terahertz Spectroscopic Imaging

    Publication Year: 2013 , Page(s): 798 - 805
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    Terahertz technologies have gained great amount of attention for biomedical imaging and tissue analysis. In this study, we utilize terahertz imaging to study the effects of hydrofluoric acid on both compact bone tissue and cartilage. We compare the differences observed in the exposure for formalin fixed and raw, dried, tissue as well as those resulting from a change in hydrofluoric (HF) concentration. Measurements are performed with THz-TDS, and a variety of spectroscopic-based image reconstruction techniques are utilized to develop contrast in the features of interest. View full abstract»

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  • Adaptive Compressed Sensing for the Fast Terahertz Reflection Tomography

    Publication Year: 2013 , Page(s): 806 - 812
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (791 KB) |  | HTML iconHTML  

    In this paper, an adaptive compressed sensing is proposed in order to enhance the performance of fast tetrahertz reflection tomography. The proposed method first acquires data at random measurement points in the spatial domain, and estimates the regions in each tomographic image where much degradation is expected. Then, it allocates additional measurement points to those regions, so that more data are acquired adaptively at the regions prone to degradation, thereby improving the quality of the reconstructed tomographic images. The proposed method was applied to the T-ray reflection tomography system, and the image quality enhancement by the proposed method, compared to the conventional method, was verified for the same number of measurement points. View full abstract»

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  • Conceiving THz Endometrial Ablation: Feasibility, Requirements and Technical Challenges

    Publication Year: 2013 , Page(s): 813 - 819
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (662 KB) |  | HTML iconHTML  

    Shallow-ablation of endometrial lining using microwaves has been traditionally indicated as a minimally invasive treatment option for dysfunctional uterine bleeding (DUB). Known as microwave endometrial ablation (MEA), relevant procedure is used as an alternative to hysterectomy considering its safety, simplicity and effectiveness. In lieu of the prevailing MEA techniques, it is attempted in this study to foresee the possibility of conceiving an alternative and a newer option on endometrial ablation using mm-wave/THz frequencies. Commensurate with this motivated impetus, objectively considered are merits and design issues of using electromagnetic (EM) spectrum of mm-wave/THz region toward optimal conversion of EM energy into a thermal ablative source so that, the basal layer of endometrium can be effectively destroyed in surgical contexts as necessary. Hence, the feasibility of designing appropriate TEA applicators for controlled and safe procedures so as to ablate just the unwanted tissues within a localized zone of energy field is addressed. Lastly, a quantitative analysis on the interaction of THz EM-energy versus the lossy dielectric characteristics of endometrial medium is indicated to model the underlying (THz-energy)-to-(thermal energy) transduction. Relevant prospects of conceiving TEA and the associated pros and cons are identified specific to the prospects of feasibility, requirement considerations and technical challenges. View full abstract»

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  • Automatic Evaluation of the 30-s Chair Stand Test Using Inertial/Magnetic-Based Technology in an Older Prefrail Population

    Publication Year: 2013 , Page(s): 820 - 827
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (503 KB) |  | HTML iconHTML  

    The aim of this study was to evaluate the inertial measures of the 30-s chair stand test using modern body-fixed motion sensors. Polynomial data fitting was used to correct the drift effect in the position estimation. Thereafter, the three most important test cycles phases (“impulse,” “stand up,” and “sit down”) were characterized and automatically analyzed. Automated test control is provided, making it possible for researchers without engineering knowledge to run the test. A collection of meaningful data based on kinematic variables is selected for further research. The proposed methodology for data analysis is a feasible tool for use in clinical settings. This method may not only improve rehabilitation therapies but also identify people at risk for falls more accurately than simply evaluating the number of cycles. View full abstract»

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  • Collection and Analysis of a Parkinson Speech Dataset With Multiple Types of Sound Recordings

    Publication Year: 2013 , Page(s): 828 - 834
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (428 KB) |  | HTML iconHTML  

    There has been an increased interest in speech pattern analysis applications of Parkinsonism for building predictive telediagnosis and telemonitoring models. For this purpose, we have collected a wide variety of voice samples, including sustained vowels, words, and sentences compiled from a set of speaking exercises for people with Parkinson's disease. There are two main issues in learning from such a dataset that consists of multiple speech recordings per subject: 1) How predictive these various types, e.g., sustained vowels versus words, of voice samples are in Parkinson's disease (PD) diagnosis? 2) How well the central tendency and dispersion metrics serve as representatives of all sample recordings of a subject? In this paper, investigating our Parkinson dataset using well-known machine learning tools, as reported in the literature, sustained vowels are found to carry more PD-discriminative information. We have also found that rather than using each voice recording of each subject as an independent data sample, representing the samples of a subject with central tendency and dispersion metrics improves generalization of the predictive model. View full abstract»

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  • A Large-Scale Clinical Validation of an Integrated Monitoring System in the Emergency Department

    Publication Year: 2013 , Page(s): 835 - 842
    Cited by:  Papers (1)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (877 KB) |  | HTML iconHTML  

    We consider an integrated patient monitoring system, combining electronic patient records with high-rate acquisition of patient physiological data. There remain many challenges in increasing the robustness of “e-health” applications to a level at which they are clinically useful, particularly in the use of automated algorithms used to detect and cope with artifact in data contained within the electronic patient record, and in analyzing and communicating the resultant data for reporting to clinicians. There is a consequential “plague of pilots,” in which engineering prototype systems do not enter into clinical use. This paper describes an approach in which, for the first time, the Emergency Department (ED) of a major research hospital has adopted such systems for use during a large clinical trial. We describe the disadvantages of existing evaluation metrics when applied to such large trials, and propose a solution suitable for large-scale validation. We demonstrate that machine learning technologies embedded within healthcare information systems can provide clinical benefit, with the potential to improve patient outcomes in the busy environment of a major ED and other high-dependence areas of patient care. View full abstract»

    Open Access
  • Investigating the Disagreement Between Clinicians’ Ratings of Patients in ICUs

    Publication Year: 2013 , Page(s): 843 - 852
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (680 KB) |  | HTML iconHTML  

    We present a Bayesian analysis of ordinal annotations made by clinicians of patients in intensive care. In particular, we investigate the different ways in which clinicians can disagree and how their disagreement is reduced once they take part in a recently proposed procedure (INSIGHT) that aims at improving consistency. The model combines a nonparametric function (loosely interpretable as the health of the patient) with clinician-specific generative procedures for producing the observed ordinal values. Our analysis provides valuable details of the rating behavior of the individual clinicians and shows that the INSIGHT procedure is particularly effective at removing (some) clinician-specific inconsistencies and biases. View full abstract»

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  • Semantic Similarity Measures in the Biomedical Domain by Leveraging a Web Search Engine

    Publication Year: 2013 , Page(s): 853 - 861
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (500 KB) |  | HTML iconHTML  

    Various researches in web related semantic similarity measures have been deployed. However, measuring semantic similarity between two terms remains a challenging task. The traditional ontology-based methodologies have a limitation that both concepts must be resided in the same ontology tree(s). Unfortunately, in practice, the assumption is not always applicable. On the other hand, if the corpus is sufficiently adequate, the corpus-based methodologies can overcome the limitation. Now, the web is a continuous and enormous growth corpus. Therefore, a method of estimating semantic similarity is proposed via exploiting the page counts of two biomedical concepts returned by Google AJAX web search engine. The features are extracted as the co-occurrence patterns of two given terms P and Q, by querying P, Q, as well as P AND Q, and the web search hit counts of the defined lexico-syntactic patterns. These similarity scores of different patterns are evaluated, by adapting support vector machines for classification, to leverage the robustness of semantic similarity measures. Experimental results validating against two datasets: dataset 1 provided by A. Hliaoutakis; dataset 2 provided by T. Pedersen, are presented and discussed. In dataset 1, the proposed approach achieves the best correlation coefficient (0.802) under SNOMED-CT. In dataset 2, the proposed method obtains the best correlation coefficient (SNOMED-CT: 0.705; MeSH: 0.723) with physician scores comparing with measures of other methods. However, the correlation coefficients (SNOMED-CT: 0.496; MeSH: 0.539) with coder scores received opposite outcomes. In conclusion, the semantic similarity findings of the proposed method are close to those of physicians' ratings. Furthermore, the study provides a cornerstone investigation for extracting fully relevant information from digitizing, free-text medical records in the National Taiwan University Hospital database. View full abstract»

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  • A Robust Algorithm for Segmenting and Tracking Clustered Cells in Time-Lapse Fluorescent Microscopy

    Publication Year: 2013 , Page(s): 862 - 869
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1594 KB) |  | HTML iconHTML  

    We present herein a robust algorithm for cell tracking in a sequence of time-lapse 2-D fluorescent microscopy images. Tracking is performed automatically via a multiphase active contours algorithm adapted to the segmentation of clustered nuclei with obscure boundaries. An ellipse fitting method is applied to avoid problems typically associated with clustered, overlapping, or dying cells, and to obtain more accurate segmentation and tracking results. We provide quantitative validation of results obtained with this new algorithm by comparing them to the results obtained from the established CellProfiler, MTrack2 (plugin for Fiji), and LSetCellTracker software. View full abstract»

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  • Information Theory-Based Automatic Multimodal Transfer Function Design

    Publication Year: 2013 , Page(s): 870 - 880
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1328 KB) |  | HTML iconHTML  

    In this paper, we present a new framework for multimodal volume visualization that combines several information-theoretic strategies to define both colors and opacities of the multimodal transfer function. To the best of our knowledge, this is the first fully automatic scheme to visualize multimodal data. To define the fused color, we set an information channel between two registered input datasets, and afterward, we compute the informativeness associated with the respective intensity bins. This informativeness is used to weight the color contribution from both initial 1-D transfer functions. To obtain the opacity, we apply an optimization process that minimizes the informational divergence between the visibility distribution captured by a set of viewpoints and a target distribution proposed by the user. This distribution is defined either from the dataset features, from manually set importances, or from both. Other problems related to the multimodal visualization, such as the computation of the fused gradient and the histogram binning, have also been solved using new information-theoretic strategies. The quality and performance of our approach are evaluated on different datasets. View full abstract»

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  • Utility of a Nonlinear Joint Dynamical Framework to Model a Pair of Coupled Cardiovascular Signals

    Publication Year: 2013 , Page(s): 881 - 890
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (856 KB) |  | HTML iconHTML  

    We have recently proposed a correlated model to provide a Gaussian mixture representation of the cardiovascular signals, with promising results in identifying rhythm disturbances. The approach provides a transformation of the data into a set of integrable Gaussians distributed over time. Looking into the model from a new joint modeling perspective, it is capable of assembling a filtered estimation, and can be used to derive temporal information of the waveforms. In this paper, we present a step-by-step derivation of the joint model putting correlation assumptions together to conclude a minimal joint description for a pair of ECG-ABP signals. We then probe novel applications of this model, including Kalman filter based denoising and fiducial point detection. In particular, we use the joint model for denoising and employ the denoised signals for pulse transit time (PTT) estimation. We analyzed more than 70 h of data from 76 patients from the MIMIC database to illustrate the accuracy of the algorithm. We have found that this method can be effectively used for robust joint ECG-ABP noise suppression, with mean signal-to-noise ratio (SNR) improvement up to 23.2 (12.0) dB and weighted diagnostic distortion measures as low as 2.1 (3.3)% for artificial (real) noises, respectively. In addition, we have estimated the error distributions for QT interval, systolic and diastolic blood pressure before and after filtering to demonstrate the maximal preservation of morphological features (ΔQT: mean ± std = 2.2 ± 6.1 ms; ΔSBP: mean ± std = 2.3 ± 1.9 mmHg; ΔDBP: mean ± std = 1.9 ± 1.4 mmHg). Finally, we have been able to present a systematic approach for robust PTT estimation (r = 0.98, p <; 0.001, mean ± std of error = -0.26 ± 2.93 ms). These findings may have important implications for reliable monitoring and estimation of clinically important features in clinical settings. In - onclusion, the proposed framework opens the door to the possibility of deploying a hybrid system that integrates these algorithmic approaches for index estimation and filtering scenarios with high output SNRs and low distortion. View full abstract»

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  • Together, we are advancing technology

    Publication Year: 2013 , Page(s): 891
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  • IEEE Xplore Digital Library

    Publication Year: 2013 , Page(s): 892
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  • IEEE Journal of Biomedical and Health Informatics (J-BHI) information for authors

    Publication Year: 2013 , Page(s): C3
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  • Table of contents

    Publication Year: 2013 , Page(s): C4
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Aims & Scope

J-BHI publishes original papers describing recent advances in the field of biomedical and health informatics where information and communication technologies intersect with health, healthcare, life sciences and biomedicine.  Papers must contain original content in theoretical analysis, methods, technical development, and/or novel clinical applications of information systems.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief

GUANG-ZHONG YANG,
Director, The Hamlyn Centre
Imperial College London, UK
g.z.yang@imperial.ac.uk
jbhi-eic@embs.org