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Biomedical Engineering, IEEE Transactions on

Issue 7 • Date July 2013

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Displaying Results 1 - 25 of 38
  • Front Cover

    Page(s): C1
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  • IEEE Transactions on Biomedical Engineering publication information

    Page(s): C2
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  • Table of Contents

    Page(s): 1765 - 1766
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  • Medical and Biological Engineering in the Next 20 Years: The Promise and the Challenges

    Page(s): 1767 - 1775
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (355 KB) |  | HTML iconHTML  

    In 2011, the American Institute for Medical and Biological Engineering (AIMBE) (www.aimbe.org) celebrated its 20th anniversary by undertaking to identify major societal challenges to which medical and biological engineers can contribute solutions in the next 20 years. This report is a summary of the six major challenges that were identified. The report also discusses some specific areas within these high-level challenges that can form the basis for policy action, provides a brief rationale for pursuing those areas, and discusses roadblocks to progress. The six overarching challenges are: 1) engineering safe and sustainable water and food supply, 2) engineering personalized health care, 3) engineering solutions to injury and chronic diseases, 4) engineering global health through infectious disease prevention and therapy, 5) engineering sustainable bioenergy production, and 6) engineering the 21st century US economy. While arrived at independently by AIMBE, many of the elements overlap with similar challenges identified by other bodies. The similarities highlight the central mission of medical and biological engineers, working with other experts, which is to solve important problems central to human health and welfare. View full abstract»

    Open Access
  • Closed-Loop Control of Renal Perfusion Pressure in Physiological Experiments

    Page(s): 1776 - 1784
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1947 KB) |  | HTML iconHTML  

    This paper presents the design, experimental modeling, and control of a pump-driven renal perfusion pressure (RPP)-regulatory system to implement precise and relatively fast RPP regulation in rats. The mechatronic system is a simple, low-cost, and reliable device to automate the RPP regulation process based on flow-mediated occlusion. Hence, the regulated signal is the RPP measured in the left femoral artery of the rat, and the manipulated variable is the voltage applied to a dc motor that controls the occlusion of the aorta. The control system is implemented in a PC through the LabView software, and a data acquisition board NI USB-6210. A simple first-order linear system is proposed to approximate the dynamics in the experiment. The parameters of the model are chosen to minimize the error between the predicted and experimental output averaged from eight input/output datasets at different RPP operating conditions. A closed-loop servocontrol system based on a pole-placement PD controller plus dead-zone compensation was proposed for this purpose. First, the feedback structure was validated in simulation by considering parameter uncertainty, and constant and time-varying references. Several experimental tests were also conducted to validate in real time the closed-loop performance for stepwise and fast switching references, and the results show the effectiveness of the proposed automatic system to regulate the RPP in the rat, in a precise, accurate (mean error less than 2 mmHg) and relatively fast mode (10-15 s of response time). View full abstract»

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  • Angular Momentum During Unexpected Multidirectional Perturbations Delivered While Walking

    Page(s): 1785 - 1795
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1598 KB) |  | HTML iconHTML  

    This study investigated the hypothesis that the coupled contribution of all body segments to the whole-body response during both walking and managing unexpected perturbations is characterized by similar features which do not depend on the laterality (i.e., right versus left sides), but can be influenced by the direction (e.g., north, east, south, etc.) of the perturbation. The whole-body angular momentum was estimated as summation of segmental angular momenta, while 15 young adults managed ten unexpected unilateral perturbations during walking. Then, the Principal component analysis was used to extract primitive features describing intersegment coordination. Results showed that intersegment coupling was similar even though the reactive response to the perturbations elicited more consistent motor schemes across body segments than during walking, especially in the frontal plane. The direction of the perturbation significantly (p <; 0.05) affected angular momentum regulation documenting the attitude of the central nervous system to interpret multiple sensory inputs in order to produce context-dependent reactive responses. With respect to the side, results highlighted anisotropic features of the elicited motor schemes that seemed to depend on subjects' dominance. Finally, results confirm that the coordination of upper and lower body segments is synergistically achieved strengthening the hypothesis that it may result from common neural pathways. View full abstract»

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  • Influence of Running Stride Frequency in Heart Rate Variability Analysis During Treadmill Exercise Testing

    Page(s): 1796 - 1805
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (797 KB) |  | HTML iconHTML  

    The analysis and interpretation of heart rate variability (HRV) during exercise is challenging not only because of the nonstationary nature of exercise, the time-varying mean heart rate, and the fact that respiratory frequency exceeds 0.4 Hz, but there are also other factors, such as the component centered at the pedaling frequency observed in maximal cycling tests, which may confuse the interpretation of HRV analysis. The objectives of this study are to test the hypothesis that a component centered at the running stride frequency (SF) appears in the HRV of subjects during maximal treadmill exercise testing, and to study its influence in the interpretation of the low-frequency (LF) and high-frequency (HF) components of HRV during exercise. The HRV of 23 subjects during maximal treadmill exercise testing is analyzed. The instantaneous power of different HRV components is computed from the smoothed pseudo-Wigner-Ville distribution of the modulating signal assumed to carry information from the autonomic nervous system, which is estimated based on the time-varying integral pulse frequency modulation model. Besides the LF and HF components, the appearance is revealed of a component centered at the running SF as well as its aliases. The power associated with the SF component and its aliases represents 22 ± 7% (median ± median absolute deviation) of the total HRV power in all the subjects. Normalized LF power decreases as the exercise intensity increases, while normalized HF power increases. The power associated with the SF does not change significantly with exercise intensity. Consideration of the running SF component and its aliases is very important in HRV analysis since stride frequency aliases may overlap with LF and HF components. View full abstract»

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  • Magnetic Fluid Hyperthermia Modeling Based on Phantom Measurements and Realistic Breast Model

    Page(s): 1806 - 1813
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (585 KB) |  | HTML iconHTML  

    Magnetic fluid hyperthermia (MFH) is a minimally invasive procedure that destroys cancer cells. It is based on a superparamagnetic heat phenomenon and consists in feeding a ferrofluid into a tumor, and then applying an external electromagnetic field, which leads to apoptosis. The strength of the magnetic field, optimal dose of the ferrofluid, the volume of the tumor and the safety standards have to be taken into consideration when MFH treatment is planned. In this study, we have presented the novel complementary investigation based both on the experiments and numerical methodology connected with female breast cancer. We have conducted experiments on simplified female breast phantoms with numerical analysis and then we transferred the results on an anatomically-like breast model. View full abstract»

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  • Coefficient-Free Blood Pressure Estimation Based on Pulse Transit Time–Cuff Pressure Dependence

    Page(s): 1814 - 1824
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (849 KB) |  | HTML iconHTML  

    Oscillometry is a popular technique for automatic estimation of blood pressure (BP). However, most of the oscillometric algorithms rely on empirical coefficients for systolic and diastolic pressure evaluation that may differ in various patient populations, rendering the technique unreliable. A promising complementary technique for automatic estimation of BP, based on the dependence of pulse transit time (PTT) on cuff pressure (CP) (PTT-CP mapping), has been proposed in the literature. However, a theoretical grounding for this technique and a nonparametric BP estimation approach are still missing. In this paper, we propose a novel coefficient-free BP estimation method based on PTT-CP dependence. PTT is mathematically modeled as a function of arterial lumen area under the cuff. It is then analytically shown that PTT-CP mappings computed from various points on the arterial pulses can be used to directly estimate systolic, diastolic, and mean arterial pressure without empirical coefficients. Analytical results are cross-validated with a pilot investigation on ten healthy subjects where 150 simultaneous electrocardiogram and oscillometric BP recordings are analyzed. The results are encouraging whereby the mean absolute errors of the proposed method in estimating systolic and diastolic pressures are 5.31 and 4.51 mmHg, respectively, relative to the Food and Drug Administration approved Omron monitor. Our work thus shows promise toward providing robust and objective BP estimation in a variety of patients and monitoring situations. View full abstract»

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  • Ontology for Heart Rate Turbulence Domain From The Conceptual Model of SNOMED-CT

    Page(s): 1825 - 1833
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (737 KB) |  | HTML iconHTML  

    Electronic health record (EHR) automates the clinician workflow, allowing evidence-based decision support and quality management. We aimed to start a framework for domain standardization of cardiovascular risk stratification into the EHR, including risk indices whose calculation involves ECG signal processing. We propose the use of biomedical ontologies completely based on the conceptual model of SNOMED-CT, which allows us to implement our domain in the EHR. In this setting, the present study focused on the heart rate turbulence (HRT) domain, according to its concise guidelines and clear procedures for parameter calculations. We used 289 concepts from SNOMED-CT, and generated 19 local extensions (new concepts) for the HRT specific concepts not present in the current version of SNOMED-CT. New concepts included averaged and individual ventricular premature complex tachograms, initial sinus acceleration for turbulence onset, or sinusal oscillation for turbulence slope. Two representative use studies were implemented: first, a prototype was inserted in the hospital information system for supporting HRT recordings and their simple follow up by medical societies; second, an advanced support for a prospective scientific research, involving standard and emergent signal processing algorithms in the HRT indices, was generated and then tested in an example database of 27 Holter patients. Concepts of the proposed HRT ontology are publicly available through a terminology server, hence their use in any information system will be straightforward due to the interoperability provided by SNOMED-CT. View full abstract»

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  • Automatic Segmentation and Measurement of Pleural Effusions on CT

    Page(s): 1834 - 1840
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (689 KB) |  | HTML iconHTML  

    Pleural effusion is an important biomarker for the diagnosis of many diseases. We develop an automated method to evaluate pleural effusion on CT scans, the measurement of which is prohibitively time consuming when performed manually. The method is based on parietal and visceral pleura extraction, active contour models, region growing, Bezier surface fitting, and deformable surface modeling. Twelve CT scans with three manual segmentations were used to validate the automatic segmentation method. The method was then applied on 91 additional scans for visual assessment. The segmentation method yielded a correlation coefficient of 0.97 and a Dice coefficient of 0.72 ± 0.13 when compared to a professional manual segmentation. The visual assessment estimated 83% cases with negligible or small segmentation errors, 14% with medium errors, and 3% with large errors. View full abstract»

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  • Spine Image Fusion Via Graph Cuts

    Page(s): 1841 - 1850
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1803 KB) |  | HTML iconHTML  

    This study investigates a novel CT/MR spine image fusion algorithm based on graph cuts. This algorithm allows physicians to visually assess corresponding soft tissue and bony detail on a single image eliminating mental alignment and correlation needed when both CT and MR images are required for diagnosis. We state the problem as a discrete multilabel optimization of an energy functional that balances the contributions of three competing terms: (1) a squared error, which encourages the solution to be similar to the MR input, with a preference to strong MR edges; (2) a squared error, which encourages the solution to be similar to the CT input, with a preference to strong CT edges; and (3) a prior, which favors smooth solutions by encouraging neighboring pixels to have similar fused-image values. We further introduce a transparency-labeling formulation, which significantly reduces the computational load. The proposed graph-cut fusion guarantees nearly global solutions, while avoiding the pix elation artifacts that affect standard wavelet-based methods. We report several quantitative evaluations/comparisons over 40 pairs of CT/MR images acquired from 20 patients, which demonstrate a very competitive performance in comparisons to the existing methods. We further discuss various case studies, and give a representative sample of the results. View full abstract»

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  • Simultaneously Identifying All True Vessels From Segmented Retinal Images

    Page(s): 1851 - 1858
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (573 KB) |  | HTML iconHTML  

    Measurements of retinal blood vessel morphology have been shown to be related to the risk of cardiovascular diseases. The wrong identification of vessels may result in a large variation of these measurements, leading to a wrong clinical diagnosis. In this paper, we address the problem of automatically identifying true vessels as a postprocessing step to vascular structure segmentation. We model the segmented vascular structure as a vessel segment graph and formulate the problem of identifying vessels as one of finding the optimal forest in the graph given a set of constraints. We design a method to solve this optimization problem and evaluate it on a large real-world dataset of 2446 retinal images. Experiment results are analyzed with respect to actual measurements of vessel morphology. The results show that the proposed approach is able to achieve 98.9% pixel precision and 98.7% recall of the true vessels for clean segmented retinal images, and remains robust even when the segmented image is noisy. View full abstract»

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  • Classification of Penetration--Aspiration Versus Healthy Swallows Using Dual-Axis Swallowing Accelerometry Signals in Dysphagic Subjects

    Page(s): 1859 - 1866
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (309 KB) |  | HTML iconHTML  

    Swallowing accelerometry is a promising noninvasive approach for the detection of swallowing difficulties. In this paper, we propose an approach for classification of swallowing accelerometry recordings containing either healthy swallows or penetration-aspiration (entry of material into the airway) in dysphagic patients. The proposed algorithm is based on the wavelet packet decomposition of swallowing accelerometry signals in combination with linear discriminant analysis as a feature reduction method and Bayes classification. The proposed algorithm was tested using swallowing accelerometry signals collected from 40 patients during the regularly scheduled videoflouroscopy exam. The participants were instructed to swallow several 5-mL sips of thin liquid barium in a head neutral position. The results of our numerical analysis showed that the proposed algorithm can differentiate healthy swallows from aspiration swallows with an accuracy greater than 90%. These results position swallowing accelerometry as a valid approach for the detection of swallowing difficulties, particularly penetration-aspiration in patients suspected of dysphagia. View full abstract»

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  • Monitoring of Cigarette Smoking Using Wearable Sensors and Support Vector Machines

    Page(s): 1867 - 1872
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (422 KB) |  | HTML iconHTML  

    Cigarette smoking is a serious risk factor for cancer, cardiovascular, and pulmonary diseases. Current methods of monitoring of cigarette smoking habits rely on various forms of self-report that are prone to errors and under reporting. This paper presents a first step in the development of a methodology for accurate and objective assessment of smoking using noninvasive wearable sensors (Personal Automatic Cigarette Tracker - PACT) by demonstrating feasibility of automatic recognition of smoke inhalations from signals arising from continuous monitoring of breathing and hand-to-mouth gestures by support vector machine classifiers. The performance of subject-dependent (individually calibrated) models was compared to performance of subject-independent (group) classification models. The models were trained and validated on a dataset collected from 20 subjects performing 12 different activities representative of everyday living (total duration 19.5 h or 21411 breath cycles). Precision and recall were used as the accuracy metrics. Group models obtained 87% and 80% of average precision and recall, respectively. Individual models resulted in 90% of average precision and recall, indicating a significant presence of individual traits in signal patterns. These results suggest the feasibility of monitoring cigarette smoking by means of a wearable and noninvasive sensor system in free living conditions. View full abstract»

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  • MSIM: Multistage Illumination Modeling of Dermatological Photographs for Illumination-Corrected Skin Lesion Analysis

    Page(s): 1873 - 1883
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1126 KB) |  | HTML iconHTML  

    Melanoma is the most deadly form of skin cancer and it is costly for dermatologists to screen every patient for melanoma. There is a need for a system to assess the risk of melanoma based on dermatological photographs of a skin lesion. However, the presence of illumination variation in the photographs can have a negative impact on lesion segmentation and classification performance. A novel multistage illumination modeling algorithm is proposed to correct the underlying illumination variation in skin lesion photographs. The first stage is to compute an initial estimate of the illumination map of the photograph using a Monte Carlo nonparametric modeling strategy. The second stage is to obtain a final estimate of the illumination map via a parametric modeling strategy, where the initial nonparametric estimate is used as a prior. Finally, the corrected photograph is obtained using the final illumination map estimate. The proposed algorithm shows better visual, segmentation, and classification results when compared to three other illumination correction algorithms, one of which is designed specifically for lesion analysis. View full abstract»

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  • A Novel Modulated Excitation Imaging System for Microultrasound

    Page(s): 1884 - 1890
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (744 KB) |  | HTML iconHTML  

    Microultrasound (micro-US), also known as ultrasound biomicroscope, is able to delineate small structures with fine spatial resolution. However, micro-US suffers limited depth of penetration due to significantly large attenuation at high frequencies. Modulated excitation imaging has displayed the capability to improve the penetration depth, while maintaining the spatial resolution. But the effectiveness of this technique in micro-US has not been fully demonstrated. In addition, the current modulated excitation imaging systems for micro-US are designed for specific excitation method, therefore, lack of flexibility, and are typically bulky and expensive. This paper presents the development of a novel system to achieve modulated excitation imaging with high programmability and flexibility to satisfy various micro-US studies. It incorporates a high-voltage arbitrary waveform generator for producing desired excitation waveform, and a programmable imaging receiver implemented by the state-of-the-art electronics and field-programmable gate array. Test results show that the proposed modulated excitation imaging system can acquire up to 20 dB signal-to-noise ratio improvement and 83% increase of penetration depth in contrast to traditional short-pulse imaging method. In vivo experiment on the dorsal skin of a human hand demonstrates good performance of the programmable modulated excitation imaging system. View full abstract»

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  • Detection of Correct and Incorrect Measurements in Real-Time Continuous Glucose Monitoring Systems by Applying a Postprocessing Support Vector Machine

    Page(s): 1891 - 1899
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1125 KB) |  | HTML iconHTML  

    Support vector machines (SVMs) are an attractive option for detecting correct and incorrect measurements in real-time continuous glucose monitoring systems (RTCGMSs), because their learning mechanism can introduce a postprocessing strategy for imbalanced datasets. The proposed SVM considers the geometric mean to obtain a more balanced performance between sensitivity and specificity. To test this approach, 23 critically ill patients receiving insulin therapy were monitored over 72 h using an RTCGMS, and a dataset of 537 samples, classified according to International Standards Organization (ISO) criteria (372 correct and 165 incorrect measurements), was obtained. The results obtained were promising for patients with septic shock or with sepsis, for which the proposed system can be considered as reliable. However, this approach cannot be considered suitable for patients without sepsis. View full abstract»

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  • Removing Ballistocardiogram Artifact From EEG Using Short- and Long-Term Linear Predictor

    Page(s): 1900 - 1911
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3156 KB) |  | HTML iconHTML  

    In this paper, a novel source extraction method is proposed for removing ballistocardiogram (BCG) artifact from EEG. BCG appears in EEG signals recorded simultaneously with functional magnetic resonance imaging. The proposed method is a semiblind source extraction algorithm based on linear prediction technique. We define a cost function according to a joint short- and long-term prediction strategy to extract the BCG sources. We call this method SLTP-BSE standing for short- and long-term prediction blind source extraction. The objective of this work is to 1) model the temporal structure of the sources using short-term prediction and 2) impose the prior information about the BCG sources using long-term prediction. These two procedures are simultaneously implemented to optimize the system. The performance of the proposed method is evaluated using both synthetic and real EEG data. The obtained results show that the proposed technique is able to remove the BCG artifact while preserving the task-related parts of the signal. The results of SLTP-BSE are compared with those of well-known BCG removal techniques confirming the superiority of the proposed method. View full abstract»

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  • Estimating Physical Assistance Need Using a Musculoskeletal Model

    Page(s): 1912 - 1919
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (562 KB) |  | HTML iconHTML  

    Technologies that provide physical assistance during tasks are often required to provide assistance specific to the task and person performing it. An example is robotic rehabilitation in which the assistance-as-needed (AAN) paradigm aims to provide operators with the minimum assistance required to perform the task. Current approaches use empirical performance-based methods which require repeated observation of the specific task before an estimate of the needed assistance can be determined. In this paper, we present a new approach utilizing a musculoskeletal model (MM) of the upper limb to estimate the operator's assistance needs with respect to physical tasks. With capabilities of the operator defined at the muscular level of the MM, an optimization model is used to estimate the operator's strength capability. Strength required to perform a task is calculated using a task model. The difference or gap between the operator's strength capability and the strength required to execute a task forms the basis for the new AAN paradigm. We show how this approach estimates the effects of limb pose, load direction, and muscle impairments on a person's ability to perform tasks. View full abstract»

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  • Real-time Estimate of Body Kinematics During a Planar Squat Task Using a Single Inertial Measurement Unit

    Page(s): 1920 - 1926
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (600 KB) |  | HTML iconHTML  

    This study aimed at the real-time estimation of the lower-limb joint and torso kinematics during a squat exercise, performed in the sagittal plane, using a single inertial measurement unit placed on the lower back. The human body was modeled with a 3-DOF planar chain. The planar IMU orientation and vertical displacement were estimated using one angular velocity and two acceleration components and a weighted Fourier linear combiner. The ankle, knee, and hip joint angles were thereafter obtained through a novel inverse kinematic module based on the use of a Jacobian pseudoinverse matrix and null-space decoupling. The aforementioned algorithms were validated on a humanoid robot for which the mechanical model used and the measured joint angles virtually exhibited no inaccuracies. Joint angles were estimated with a maximal error of 1.5°. The performance of the proposed analytical and experimental methodology was also assessed by conducting an experiment on human volunteers and by comparing the relevant results with those obtained through the more conventional photogrammetric approach. The joint angles provided by the two methods displayed differences equal to 3 ± 1°. These results, associated with the real-time capability of the method, open the door to future field applications in both rehabilitation and sport. View full abstract»

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  • Interpolated Average CT for Attenuation Correction in PET—A Simulation Study

    Page(s): 1927 - 1934
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (517 KB) |  | HTML iconHTML  

    Previously, we proposed using an interpolated average CT (IACT) method for attenuation correction (AC) in positron emission tomography (PET), which is a good, low-dose approximation of cine average CT (CACT) to reduce misalignments and improve quantification in PET/CT. This study aims to evaluate the performance of IACT for different motion amplitudes. We used the digital four-dimensional (4-D) extended cardiac-torso phantom (XCAT) to simulate maximum of 2, 3, and 4 cm respiratory motions. The respiratory cycle was divided into 13 phases, with average activity and attenuation maps to represent 18F-fluorodeoxyglucose (18F-FDG) distributions with average respiratory motions and CACT, respectively. The end-inspiration, end-expiration, and midrespiratory phases of the XCAT attenuation maps represented three different helical CTs (i.e., HCT-1, HCT-5, and HCT-8). The IACTs were generated using: 1) 2 extreme + 11 interpolated phases (IACT2o); 2) 2 phases right after the extreme phases + 11 interpolated phases (IACT2s); 3) 4 original + 9 interpolated phases (IACT4o). A spherical lesion with a target-to-background ratio (TBR) of 4:1 and a diameter of 25 mm was placed in the base of right lung. The noise-free and noisy sinograms with attenuation modeling were generated and reconstructed with different noise-free and noisy AC maps (CACT, HCTs, and IACTs) by Software for Tomographic Image Reconstruction, respectively, using ordered subset expectation maximization(OS-EM) with up to 300 updates. Normalized mean-square error, mutual information (MI), TBR, image profile, and noise-contrast tradeoff were analyzed. The PET reconstructed images with AC using CACT showed least difference as compared to the original phantom, followed by IACT 4o, IACT2o , IACT2s, HCT-5, HCT-8, and HCT-1. Significant artifacts were observed in the reconstructed images using HCTs for AC. The MI differences betweenIACT - sub>2o and IACT4o/CACT were <;0.41% and <;2.17%, respectively.With a slight misplacement of the two extreme phases, IACT2s was still comparable to IACT 2o with MI difference of <;2.23%. The IACT is a robust and accurate low-dose alternate to CACT. View full abstract»

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  • Estimating Skeletal Muscle Fascicle Curvature From B-Mode Ultrasound Image Sequences

    Page(s): 1935 - 1945
    Multimedia
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3934 KB) |  | HTML iconHTML  

    We address the problem of tracking in vivo muscle fascicle shape and length changes using ultrasound video sequences. Quantifying fascicle behavior is required to improve understanding of the functional significance of a muscle's geometric properties. Ultrasound imaging provides a noninvasive means of capturing information on fascicle behavior during dynamic movements; to date however, computational approaches to assess such images are limited. Our approach to the problem is novel because we permit fascicles to take up nonlinear shape configurations. We achieve this using a Bayesian tracking framework that is: 1) robust, conditioning shape estimates on the entire history of image observations; and 2) flexible, enforcing only a very weak Gaussian Process shape prior that requires fascicles to be locally smooth. The method allows us to track and quantify fascicle behavior in vivo during a range of movements, providing insight into dynamic changes in muscle geometric properties which may be linked to patterns of activation and intramuscular forces and pressures. View full abstract»

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  • Multiparameter Respiratory Rate Estimation From the Photoplethysmogram

    Page(s): 1946 - 1953
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (623 KB) |  | HTML iconHTML  

    We present a novel method for estimating respiratory rate in real time from the photoplethysmogram (PPG) obtained from pulse oximetry. Three respiratory-induced variations (frequency, intensity, and amplitude) are extracted from the PPG using the Incremental-Merge Segmentation algorithm. Frequency content of each respiratory-induced variation is analyzed using fast Fourier transforms. The proposed Smart Fusion method then combines the results of the three respiratory-induced variations using a transparent mean calculation. It automatically eliminates estimations considered to be unreliable because of detected presence of artifacts in the PPG or disagreement between the different individual respiratory rate estimations. The algorithm has been tested on data obtained from 29 children and 13 adults. Results show that it is important to combine the three respiratory-induced variations for robust estimation of respiratory rate. The Smart Fusion showed trends of improved estimation (mean root mean square error 3.0 breaths/min) compared to the individual estimation methods (5.8, 6.2, and 3.9 breaths/min). The Smart Fusion algorithm is being implemented in a mobile phone pulse oximeter device to facilitate the diagnosis of severe childhood pneumonia in remote areas. View full abstract»

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  • 3-D Reconstruction of the Spine From Biplanar Radiographs Based on Contour Matching Using the Hough Transform

    Page(s): 1954 - 1964
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (825 KB) |  | HTML iconHTML  

    The purpose of this study was to develop and evaluate a method for three-dimensional (3-D) reconstruction of the spine from biplanar radiographs. The approach was based on vertebral contour matching for estimating vertebral orientations and locations. Vertebral primitives were initially positioned under constraint of the 3-D spine midline, which was estimated from manually identified control points. Vertebral orientations and locations were automatically adjusted by matching projections of 3-D primitives with vertebral edges on biplanar radiographs based on the generalized Hough transform technique with a deformation tolerant matching strategy. We used graphics processing unit to accelerate reconstruction. Accuracy and precision were evaluated using radiographs from 15 scoliotic patients and a spine model in 24 poses. On in vivo radiographs, accuracy was within 2.8° for orientation and 2.4 mm for location; precision was within 2.3° for orientation and 2.1 mm for location. results were slightly better on model radiographs than on in vivo radiographs but without significance (p > 0.05). The duration for user intervention was less than 2 min, and the computation time was within 3 min. Results indicated the method's reliability. It is a promising tool to determine 3-D spinal geometry with acceptable user interaction. 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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Editor-in-Chief
Bin He
Department of Biomedical Engineering