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Biomedical Engineering, IEEE Transactions on

Issue 7 • Date July 2010

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Displaying Results 1 - 25 of 38
  • Table of contents

    Publication Year: 2010 , Page(s): C1
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  • IEEE Transactions on Biomedical Engineering publication information

    Publication Year: 2010 , Page(s): C2
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  • Table of contents

    Publication Year: 2010 , Page(s): 1529 - 1530
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  • Estimation of Three- and Four-Element Windkessel Parameters Using Subspace Model Identification

    Publication Year: 2010 , Page(s): 1531 - 1538
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (346 KB) |  | HTML iconHTML  

    A windkessel model is widely used to operationalize vascular characteristics. In this paper, we employ a noniterative subspace model identification (SMI) algorithm to estimate parameters in a three- and four-element windkessel model by application of physical foreknowledge. Simulation data of the systemic circulation were used to investigate systematic and random errors in the parameter estimations. Results were compared with different methods as proposed in the literature: one closed-loop and two iterative methods for the three-element model, and one iterative method for the four-element model. For the three-element model, no significant systematic errors were observed using SMI. Concerning random errors, SMI appeared more robust in parameter estimations compared with the other methods ( P <; 0.05 for a signal-to-noise ratio of 18 dB). For the four-element model, a significant systematic error in the estimate of the arterial inertance L was observed (P = 0.011). However, for all methods, an increasing number of outliers in parameter estimates were observed at increased noise levels. These outliers were almost exclusive due to errors in estimates of L. In conclusion, with SMI physical parameters can mathematically be derived by application of physiological foreknowledge. For a three-element windkessel model, SMI appeared a very robust method to estimate parameters. However, application to a four-element windkessel model was less accurate because of low identifiability of L. Therefore, based on the simulation results, the use of the four-element windkessel model is questionable. View full abstract»

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  • A Simulation Tool to Study High-Frequency Chest Compression Energy Transfer Mechanisms and Waveforms for Pulmonary Disease Applications

    Publication Year: 2010 , Page(s): 1539 - 1546
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (295 KB) |  | HTML iconHTML  

    High-frequency chest compression (HFCC) can be used as a therapeutic intervention to assist in the transport and clearance of mucus and enhance water secretion for cystic fibrosis patients. An HFCC pump-vest and half chest-lung simulation, with 23 lung generations, has been developed using inertance, compliance, viscous friction relationships, and Newton's second law. The simulation has proven to be useful in studying the effects of parameter variations and nonlinear effects on HFCC system performance and pulmonary system response. The simulation also reveals HFCC waveform structure and intensity changes in various segments of the pulmonary system. The HFCC system simulation results agree with measurements, indicating that the HFCC energy transport mechanism involves a mechanically induced pulsation or vibration waveform with average velocities in the lung that are dependent upon small air displacements over large areas associated with the vest-chest interface. In combination with information from lung physiology, autopsies and a variety of other lung modeling efforts, the results of the simulation can reveal a number of therapeutic implications. View full abstract»

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  • Exploring Cross-Species-Related miRNAs Based on Sequence and Secondary Structure

    Publication Year: 2010 , Page(s): 1547 - 1553
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (488 KB) |  | HTML iconHTML  

    MicroRNA (miRNA) plays an important role as a regulator of mRNA. But how miRNAs relate with each other in gene regulation network is still remaining. Understanding the reactions between miRNAs can be very significant for exploring miRNA target, gene regulation mechanism, and gene conservation in evolution process. We explore cross-species-related miRNAs to find out how miRNAs regulate each other by using joint entropy and mutual information, respectively. Our contribution includes the following: 1) our algorithms are based on the combination of sequence and secondary structure analysis because miRNAs are conserved much better in the secondary structure; and 2) when we consider if two miRNAs A and B are related, we consider the relationship between A (B) and other miRNAs in their own species too. If A (B) has a very close relationship with other miRNAs in its own species and the relationship of A and B is close too, then the relationship between A and B is more important. Therefore, this related miRNA pair is more significant. So, our algorithms confirm to the reality that genes regulate each other as a network. Through experiments on miRNAMap 2.0, it has been proven that we can not only find out the known related miRNA pairs but also predict some novel ones. View full abstract»

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  • Nonlinear Dynamic Modeling of Isometric Force Production in Primate Eye Muscle

    Publication Year: 2010 , Page(s): 1554 - 1567
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (776 KB) |  | HTML iconHTML  

    Although the oculomotor plant is usually modeled as a linear system, recent studies of ocular motoneuron behavior have drawn attention to the presence of significant nonlinearities. One source of these is the development of muscle force in response to changes in motoneuron firing rate. Here, we attempt to simulate the production of isometric force by the primate lateral rectus muscle in response to electrical stimulation [A. Fuchs and E. Luschei, “Development of isometric tension in simian extraocular muscle,” J. Physiol., vol. 219, no. 1, pp. 155-166, 1971] by comparing four different modeling approaches. The data could be well fitted either by parameter estimation for physically based models of force production [J. Bobet, E. R. Gossen, and R. B. Stein, “A comparison of models of force production during stimulated isometric ankle dorsiflexion in humans,” IEEE Trans. Neural Syst. Rehabil. Eng., vol. 13, no. 4, pp. 444-451, Dec. 2005; E. Mavritsaki, N. Lepora, J. Porrill, C. H. Yeo, and P. Dean, “Response linearity determined by recruitment strategy in detailed model of nictitating membrane control,” Biol. Cybern., vol. 96, no. 1, pp. 39-57, 2007], or by the application of a generic method for nonlinear system identification (the nonlinear autoregressive with exogenous input (NARX) model). These results suggest that nonlinear system identification may be a useful method for modeling more general aspects of muscle function, and provide a basis for distributed models of motor units in extraocular muscle for understanding dynamic oculomotor control. The success of previous linear models points to the potential importance of motor unit recruitment in overcoming nonlinearities in the oculomotor plant. View full abstract»

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  • Ranking the Influence of Tissue Conductivities on Forward-Calculated ECGs

    Publication Year: 2010 , Page(s): 1568 - 1576
    Cited by:  Papers (16)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (679 KB) |  | HTML iconHTML  

    This paper examined the effects that different tissue conductivities had on forward-calculated ECGs. To this end, we ranked the influence of tissues by performing repetitive forward calculations while varying the respective tissue conductivity. The torso model included all major anatomical structures like blood, lungs, fat, anisotropic skeletal muscle, intestine, liver, kidneys, bone, cartilage, and spleen. Cardiac electrical sources were derived from realistic atrial and ventricular simulations. The conductivity rankings were based on one of two methods: First, we considered fixed percental conductivity changes to probe the sensitivity of the ECG regarding conductivity alterations. Second, we set conductivities to the reported minimum and maximum values to evaluate the effects of the existing conductivity uncertainties. The amplitudes of both atrial and ventricular ECGs were most sensitive for blood, skeletal muscle conductivity and anisotropy as well as for heart, fat, and lungs. If signal morphology was considered, fat was more important whereas skeletal muscle was less important. When comparing atria and ventricles, the lungs had a larger effect on the atria yet the heart conductivity had a stronger impact on the ventricles. The effects of conductivity uncertainties were significant. Future studies dealing with electrocardiographic simulations should consider these effects. View full abstract»

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  • Model-Based Assessment of Tissue Perfusion and Temperature in Deep Hypothermic Patients

    Publication Year: 2010 , Page(s): 1577 - 1586
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (653 KB) |  | HTML iconHTML  

    Deep hypothermic circulatory arrest is necessary for some types of cardiac and aortic surgery. Perfusion of the brain can be maintained using a heart-lung machine and unilateral antegrade cerebral perfusion. Cooling rates during extracorporeal circulation depend on local perfusion. A core temperature of 24 °C-25 °C is aimed at to extend ischemic tolerance of tissues. Information on cerebral perfusion and temperature is important for the safety of patients, but hardly accessible to measurement. A combined simulation model of hemodynamics and temperature is presented in this paper. The hemodynamics model employs the transmission-line approach and integrates the Circle of Willis (CoW). This allows for parameterization of individual aberrations. Simulation results of cerebral perfusion are shown for two configurations of the CoW. The temperature model provides spatial information on temperature fields. It considers heat transfer in the various tissues retrieving data of local tissue perfusion from the hemodynamics model. The combined model is evaluated by retrospective simulation of two aortic operations. View full abstract»

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  • Prediction of Acoustic Feature Parameters Using Myoelectric Signals

    Publication Year: 2010 , Page(s): 1587 - 1595
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (644 KB) |  | HTML iconHTML  

    It is well-known that a clear relationship exists between human voices and myoelectric signals (MESs) from the area of the speaker's mouth. In this study, we utilized this information to implement a speech synthesis scheme in which MES alone was used to predict the parameters characterizing the vocal-tract transfer function of specific speech signals. Several feature parameters derived from MES were investigated to find the optimal feature for maximization of the mutual information between the acoustic and the MES features. After the optimal feature was determined, an estimation rule for the acoustic parameters was proposed, based on a minimum mean square error (MMSE) criterion. In a preliminary study, 60 isolated words were used for both objective and subjective evaluations. The results showed that the average Euclidean distance between the original and predicted acoustic parameters was reduced by about 30% compared with the average Euclidean distance of the original parameters. The intelligibility of the synthesized speech signals using the predicted features was also evaluated. A word-level identification ratio of 65.5% and a syllable-level identification ratio of 73% were obtained through a listening test. View full abstract»

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  • Analysis of Wheezes Using Wavelet Higher Order Spectral Features

    Publication Year: 2010 , Page(s): 1596 - 1610
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (743 KB) |  | HTML iconHTML  

    Wheezes are musical breath sounds, which usually imply an existing pulmonary obstruction, such as asthma and chronic obstructive pulmonary disease (COPD). Although many studies have addressed the problem of wheeze detection, a limited number of scientific works has focused in the analysis of wheeze characteristics, and in particular, their time-varying nonlinear characteristics. In this study, an effort is made to reveal and statistically analyze the nonlinear characteristics of wheezes and their evolution over time, as they are reflected in the quadratic phase coupling of their harmonics. To this end, the continuous wavelet transform (CWT) is used in combination with third-order spectra to define the analysis domain, where the nonlinear interactions of the harmonics of wheezes and their time variations are revealed by incorporating instantaneous wavelet bispectrum and bicoherence, which provide with the instantaneous biamplitude and biphase curves. Based on this nonlinear information pool, a set of 23 features is proposed for the nonlinear analysis of wheezes. Two complementary perspectives, i.e., general and detailed, related to average performance and to localities, respectively, were used in the construction of the feature set, in order to embed trends and local behaviors, respectively, seen in the nonlinear interaction of the harmonic elements of wheezes over time. The proposed feature set was evaluated on a dataset of wheezes, acquired from adult patients with diagnosed asthma and COPD from a lung sound database. The statistical evaluation of the feature set revealed discrimination ability between the two pathologies for all data subgroupings. In particular, when the total breathing cycle was examined, all 23 features, but one, showed statistically significant difference between the COPD and asthma pathologies, whereas for the subgroupings of inspiratory and expiratory phases, 18 out of 23 and 22 out of 23 features exhibited discrimination power, respectively.- - This paves the way for the use of the wavelet higher order spectral features as an input vector to an efficient classifier. Apparently, this would integrate the intrinsic characteristics of wheezes within computerized diagnostic tools toward their more efficient evaluation. View full abstract»

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  • Prediction of Intradialytic Hypotension Using Photoplethysmography

    Publication Year: 2010 , Page(s): 1611 - 1619
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (218 KB) |  | HTML iconHTML  

    Intradialytic hypotension is the most common acute complication during conventional hemodialysis treatment. Prediction of such events is highly desirable in clinical routine for prevention. This paper presents a novel prediction method of acute symptomatic hypotension in which the photoplethysmographic signal is analyzed with respect to changes in amplitude, reflecting vasoconstriction, and cardiac output. The method is based on a statistical model in which the noise is assumed to have Laplacian amplitude distribution. The performance is evaluated on 11 hypotension-prone patients who underwent hemodialysis treatment, resulting in seven events with acute symptomatic hypotension and 17 without. The photoplethysmographic signal was continuously acquired during treatment as was information on blood pressure and oxygen saturation. Using leave-one-out cross validation, the proposed method predicted six out of seven hypotensive events, while producing 1 false prediction out of 17 possible. The performance was achieved when the prediction threshold was chosen to be in the range 57%-65% of the photoplethysmographic envelope at treatment onset. View full abstract»

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  • A Sparse Representation Method for Magnetic Resonance Spectroscopy Quantification

    Publication Year: 2010 , Page(s): 1620 - 1627
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (355 KB) |  | HTML iconHTML  

    In this paper, a sparse representation method is proposed for magnetic resonance spectroscopy (MRS) quantification. An observed MR spectrum is composed of a set of metabolic spectra of interest, a baseline and a noise. To separate the spectra of interest, the a priori knowledge about these spectra, such as signal models, the peak frequencies, and linewidth ranges of different resonances, is first integrated to construct a dictionary. The separation of the spectra of interest is then performed by using a pursuit algorithm to find their sparse representations with respect to the dictionary. For the challenging baseline problem, a wavelet filter is proposed to filter the smooth and broad components of both the observed spectra and the basis functions in the dictionary. The computation of sparse representation can then be carried out by using the remaining data. Simulation results show the good performance of this wavelet filtering-based strategy in separating the overlapping components between the baselines and the spectra of interest, when no appropriate model function for the baseline is available. Quantifications of in vivo brain MR spectra from tumor patients in different stages of progression demonstrate the effectiveness of the proposed method. View full abstract»

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  • Nonlinear Bayesian Filtering for Denoising of Electrocardiograms Acquired in a Magnetic Resonance Environment

    Publication Year: 2010 , Page(s): 1628 - 1638
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (700 KB) |  | HTML iconHTML  

    ECGs are currently acquired during magnetic resonance examinations. This “hostile” environment highly distorts ECG signals, due to the high-static magnetic field, RF pulses and fast switching magnetic gradients. Specific signal processing is then required since the ECG signal is used for image synchronization with heart activity (or triggering) and for patient monitoring. A new set of two magnetic field gradient (MFG) artifact reduction methods, based on ECG and MFG artifact modelings and Bayesian filtering, is herein presented and will be called Bayesian gradient artifact reduction monitoring (BAGARRE-M) and BAGARRE-triggering. These algorithms overcome the limitations of state-of-the-art methods and enable accurate processing of very noisy ECG acquisitions during MRI. Whether for triggering or monitoring purposes, the presented methods overcome state-of-the-art techniques with both better QRS detection accuracy and signal denoising quality. View full abstract»

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  • Automated Real-Time Epileptic Seizure Detection in Scalp EEG Recordings Using an Algorithm Based on Wavelet Packet Transform

    Publication Year: 2010 , Page(s): 1639 - 1651
    Cited by:  Papers (22)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (364 KB) |  | HTML iconHTML  

    A novel wavelet-based algorithm for real-time detection of epileptic seizures using scalp EEG is proposed. In a moving-window analysis, the EEG from each channel is decomposed by wavelet packet transform. Using wavelet coefficients from seizure and nonseizure references, a patient-specific measure is developed to quantify the separation between seizure and nonseizure states for the frequency range of 1-30 Hz. Utilizing this measure, a frequency band representing the maximum separation between the two states is determined and employed to develop a normalized index, called combined seizure index (CSI). CSI is derived for each epoch of every EEG channel based on both rhythmicity and relative energy of that epoch as well as consistency among different channels. Increasing significantly during ictal states, CSI is inspected using one-sided cumulative sum test to generate proper channel alarms. Analyzing alarms from all channels, a seizure alarm is finally generated. The algorithm was tested on scalp EEG recordings from 14 patients, totaling 75.8 h with 63 seizures. Results revealed a high sensitivity of 90.5% , a false detection rate of 0.51 h-1 and a median detection delay of 7 s. The algorithm could also lateralize the focus side for patients with temporal lobe epilepsy. View full abstract»

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  • Magnetoencephalography Source Localization Using the Source Affine Image Reconstruction (SAFFIRE) Algorithm

    Publication Year: 2010 , Page(s): 1652 - 1662
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1139 KB) |  | HTML iconHTML  

    Nonparametric iterative algorithms have been previously proposed to achieve high-resolution, sparse solutions to the bioelectromagnetic inverse problem applicable to multichannel magnetoencephalography and EEG recordings. Using a mmse estimation framework, we propose a new algorithm of this type denoted as source affine image reconstruction (SAFFIRE) aiming to reduce the vulnerability to initialization bias, augment robustness to noise, and decrease sensitivity to the choice of regularization. The proposed approach operates in a normalized lead-field space and employs an initial estimate based on matched filtering to combat the potential biasing effect of previously proposed initialization methods. SAFFIRE minimizes difficulties associated with the selection of the most appropriate regularization parameter by using two separate loading terms: a fixed noise-dependent term that can be directly estimated from the data and arises naturally from the mmse formulation, and an adaptive term (adjusted according to the update of the source estimate) that accounts for uncertainties of the forward model in real-experimental applications. We also show that a noncoherent integration scheme can be used within the SAFFIRE algorithm structure to further enhance the reconstruction accuracy and improve robustness to noise. View full abstract»

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  • Self-Calibration of Biplanar Radiographic Images Through Geometric Spine Shape Descriptors

    Publication Year: 2010 , Page(s): 1663 - 1675
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1040 KB) |  | HTML iconHTML  

    This paper presents a novel self-calibration method of an X-ray scene applied for the 3-D reconstruction of the scoliotic spine. Current calibration techniques either use a cumbersome calibration apparatus or depend on manually identified landmarks to determine the geometric configuration, thus limiting routine clinical evaluation. The proposed approach uses high-level information automatically extracted from biplanar X-rays to solve the radiographic scene parameters. We first present a segmentation method that takes into account the variable appearance and geometry of a scoliotic spine in order to isolate and extract the silhouettes of the anterior vertebral body. By incorporating prior anatomical information through a Bayesian formulation of the morphological distribution, a multiscale spine segmentation framework is proposed for scoliotic patients. An iterative nonlinear optimization procedure, integrating a 3-D visual hull reconstruction and geometrical torsion properties of the spine, is then applied to globally refine the geometrical parameters of the 3-D viewing scene and obtain the optimal 3-D reconstruction. An experimental comparison with data provided from reference synthetic models yields similar accuracy on the retroprojection of low-level primitives such as anatomical landmarks identified on each vertebra (2.2 mm). Results obtained from a clinical validation on 60 pairs of uncalibrated digitized X-rays of adolescents with scoliosis show that the 3-D reconstructions from the new system offer geometrically accurate models with insignificant differences for 3-D clinical indexes commonly used in the evaluation of spinal deformities. The reported experiments demonstrate a viable and accurate alternative to previous reconstruction techniques, offering the first automatic approach for routine 3-D clinical assessment in radiographic suites. View full abstract»

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  • Expectation–Maximization-Driven Geodesic Active Contour With Overlap Resolution (EMaGACOR): Application to Lymphocyte Segmentation on Breast Cancer Histopathology

    Publication Year: 2010 , Page(s): 1676 - 1689
    Cited by:  Papers (23)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1576 KB) |  | HTML iconHTML  

    The presence of lymphocytic infiltration (LI) has been correlated with nodal metastasis and tumor recurrence in HER2+ breast cancer (BC). The ability to automatically detect and quantify extent of LI on histopathology imagery could potentially result in the development of an image based prognostic tool for human epidermal growth factor receptor-2 (HER2+) BC patients. Lymphocyte segmentation in hematoxylin and eosin (H&E) stained BC histopathology images is complicated by the similarity in appearance between lymphocyte nuclei and other structures (e.g., cancer nuclei) in the image. Additional challenges include biological variability, histological artifacts, and high prevalence of overlapping objects. Although active contours are widely employed in image segmentation, they are limited in their ability to segment overlapping objects and are sensitive to initialization. In this paper, we present a new segmentation scheme, expectation-maximization (EM) driven geodesic active contour with overlap resolution (EMaGACOR), which we apply to automatically detecting and segmenting lymphocytes on HER2+ BC histopathology images. EMaGACOR utilizes the expectation-maximization algorithm for automatically initializing a geodesic active contour (GAC) and includes a novel scheme based on heuristic splitting of contours via identification of high concavity points for resolving overlapping structures. EMaGACOR was evaluated on a total of 100 HER2+ breast biopsy histology images and was found to have a detection sensitivity of over 86% and a positive predictive value of over 64%. By comparison, the EMaGAC model (without overlap resolution) and GAC model yielded corresponding detection sensitivities of 42% and 19%, respectively. Furthermore, EMaGACOR was able to correctly resolve over 90% of overlaps between intersecting lymphocytes. Hausdorff distance (HD) and mean absolute distance (MAD) for EMaGACOR were found to be 2.1 and 0.9 pixels, respectively, and significantly better compa- - red to the corresponding performance of the EMaGAC and GAC models. EMaGACOR is an efficient, robust, reproducible, and accurate segmentation technique that could potentially be applied to other biomedical image analysis problems. View full abstract»

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  • A Computer-Aided Diagnosis System of Nuclear Cataract

    Publication Year: 2010 , Page(s): 1690 - 1698
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (673 KB) |  | HTML iconHTML  

    Cataracts are the leading cause of blindness worldwide, and nuclear cataract is the most common form of cataract. An algorithm for automatic diagnosis of nuclear cataract is investigated in this paper. Nuclear cataract is graded according to the severity of opacity using slit lamp lens images. Anatomical structure in the lens image is detected using a modified active shape model. On the basis of the anatomical landmark, local features are extracted according to clinical grading protocol. Support vector machine regression is employed for grade prediction. This is the first time that the nucleus region can be detected automatically in slit lamp images. The system is validated using clinical images and clinical ground truth on >5000 images. The success rate of structure detection is 95% and the average grading difference is 0.36 on a 5.0 scale. The automatic diagnosis system can improve the grading objectivity and potentially be used in clinics and population studies to save the workload of ophthalmologists. View full abstract»

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  • Quantitative Analysis of Protective Effect of Erythropoietin on Diabetic Retinal Cells Using Molecular Hyperspectral Imaging Technology

    Publication Year: 2010 , Page(s): 1699 - 1706
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (397 KB) |  | HTML iconHTML  

    A molecular hyperspectral imaging (MHI) system was developed to evaluate the protective effects of erythropoietin (EPO) on early diabetic retinopathy in rats. The system was used to capture hyperspectral images of rat retinal sections selected from three groups: normal control, diabetic, and EPO. Three biochemical parameters were defined, namely, the spectral transmittance index, thickness of outer nuclear layer, and cell area percentage. The corresponding algorithms to calculate these were likewise presented. Experimental results show that, after treatment, the newly defined biochemical parameters of the EPO group become more similar to those of the normal control group compared with those of the diabetic group. This indicates that, to some degree, EPO provides protective effects on the retinal cells of chemically induced diabetic rats after it is injected intravitreally at the onset of diabetes. The results likewise show that the MHI system could provide useful quantitative information regarding retinal sections, which ophthalmologists can use to determine the pathogenesis of diabetic retinopathy and evaluate the protective effect of EPO on diabetic retinal cells. View full abstract»

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  • A Partial Intensity Invariant Feature Descriptor for Multimodal Retinal Image Registration

    Publication Year: 2010 , Page(s): 1707 - 1718
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (711 KB) |  | HTML iconHTML  

    Detection of vascular bifurcations is a challenging task in multimodal retinal image registration. Existing algorithms based on bifurcations usually fail in correctly aligning poor quality retinal image pairs. To solve this problem, we propose a novel highly distinctive local feature descriptor named partial intensity invariant feature descriptor (PIIFD) and describe a robust automatic retinal image registration framework named Harris-PIIFD. PIIFD is invariant to image rotation, partially invariant to image intensity, affine transformation, and viewpoint/perspective change. Our Harris-PIIFD framework consists of four steps. First, corner points are used as control point candidates instead of bifurcations since corner points are sufficient and uniformly distributed across the image domain. Second, PIIFDs are extracted for all corner points, and a bilateral matching technique is applied to identify corresponding PIIFDs matches between image pairs. Third, incorrect matches are removed and inaccurate matches are refined. Finally, an adaptive transformation is used to register the image pairs. PIIFD is so distinctive that it can be correctly identified even in nonvascular areas. When tested on 168 pairs of multimodal retinal images, the Harris-PIIFD far outperforms existing algorithms in terms of robustness, accuracy, and computational efficiency. View full abstract»

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  • A Bayesian Reconstruction Method with Marginalized Uncertainty Model for Camera Motion in Microrotation Imaging

    Publication Year: 2010 , Page(s): 1719 - 1728
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (522 KB) |  | HTML iconHTML  

    Reconstruction of a 3-D structure from multiple projection images requires prior knowledge of projection directions or camera motion parameters that describe the relative positions and orientations of 3-D structure with respect to the camera. These parameters can be estimated using, for instance, the conventional correlation alignment and feature-based methods. However, the alignment methods are not perfect, where the inaccuracy of the estimated motion parameters causes artifacts in the reconstruction. To overcome this problem, we propose a Bayesian approach to reconstruct the object that takes the motion uncertainty distribution into account. Moreover, we consider the motion parameters as nuisance parameters and integrate them out from the posterior distribution, assuming a Gaussian uncertainty model, which yields a statistical cost function to be minimized. The proposed method is applied in microrotation fluorescence imaging, where we aim at 3-D reconstruction of a rotating object from an image series, acquired by an optical microscope. The experiments with simulated and real microrotation datasets demonstrate that the proposed method provides visually and numerically better results than the traditional reconstruction methods, which ignore the uncertainty of the motion estimates. View full abstract»

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  • Effect of MR Distortion on Targeting for Deep-Brain Stimulation

    Publication Year: 2010 , Page(s): 1729 - 1735
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (397 KB) |  | HTML iconHTML  

    Deep-brain stimulation (DBS) surgery involves placing electrodes within specific deep-brain target nuclei. Surgeons employ MR imaging for preoperative selection of targets and computed tomography (CT) imaging for designing stereotactic frames used for intraoperative placement of electrodes at the targets. MR distortion may contribute to target-selection error in the MR scan and also to MR-CT registration error, each of which contributes to error in electrode placement. In this paper, we analyze the error contributed by the MR distortion to the total DBS targeting error. Distortion in conventional MR scans, both T1 and T2 weighted, were analyzed for six bilateral DBS patients in the typical areas of brain using typical scans on a 3-T clinical scanner. Mean targeting error due to MR distortion in T2 was found to be 0.07 ± 0.025 mm with a maximum of 0.13 mm over 12 targets; error in the T1 images was smaller by 4%. View full abstract»

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  • Vaginal Tactile Imaging

    Publication Year: 2010 , Page(s): 1736 - 1744
    Cited by:  Papers (4)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (778 KB) |  | HTML iconHTML  

    Changes in the elasticity of the vaginal walls, connective support tissues, and muscles are thought to be significant factors in the development of pelvic organ prolapse, a highly prevalent condition affecting at least 50% of women in the United States during their lifetimes. It creates two predominant concerns specific to the biomechanical properties of pelvic support tissues: how does tissue elasticity affect the development of pelvic organ prolapse and how can functional elasticity be maintained through reconstructive surgery. We designed a prototype of vaginal tactile imager (VTI) for visualization and assessment of elastic properties of pelvic floor tissues. In this paper, we analyze applicability of tactile imaging for evaluation of reconstructive surgery results and characterization of normal and pelvic organ prolapse conditions. A pilot clinical study with 13 patients demonstrated that VTI allows imaging of vaginal walls with increased rigidity due to implanted mesh grafts following reconstructive pelvic surgery and VTI has the potential for prolapse characterization and detection. View full abstract»

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  • A MRI and Polarized Gases Compatible Respirator and Gas Administrator for the Study of the Small Animal Lung: Volume Measurement and Control

    Publication Year: 2010 , Page(s): 1745 - 1749
    Cited by:  Papers (1)
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    We have developed over the past years an experimental magnetic resonance imaging (MRI) and polarized gases compatible mechanical respirator for the study of the small experimental animal. The respirator has been successfully used for experiments both in the MRI setting for polarized 3He, 19F, and proton imaging as well as for functional measurements of the lungs. The new main pneumatic valve with the two integrated sensors for simultaneous lung pressure and volume measurements and the proportional valve to set the tidal volume of the respiration are described. It is shown how the device measures and controls the tidal volume of the lungs. View full abstract»

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Aims & Scope

IEEE Transactions on Biomedical Engineering contains basic and applied papers dealing with biomedical engineering. Papers range from engineering development in methods and techniques with biomedical applications to experimental and clinical investigations with engineering contributions.

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Meet Our Editors

Editor-in-Chief
Bin He
Department of Biomedical Engineering