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COMPUTER SCIENCE (1196 journals)                  1 2 3 4 5 6 | Last

Showing 1 - 200 of 872 Journals sorted alphabetically
3D Printing and Additive Manufacturing     Full-text available via subscription   (Followers: 20)
Abakós     Open Access   (Followers: 4)
ACM Computing Surveys     Hybrid Journal   (Followers: 22)
ACM Journal on Computing and Cultural Heritage     Hybrid Journal   (Followers: 8)
ACM Journal on Emerging Technologies in Computing Systems     Hybrid Journal   (Followers: 11)
ACM Transactions on Accessible Computing (TACCESS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Algorithms (TALG)     Hybrid Journal   (Followers: 15)
ACM Transactions on Applied Perception (TAP)     Hybrid Journal   (Followers: 5)
ACM Transactions on Architecture and Code Optimization (TACO)     Hybrid Journal   (Followers: 9)
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 7)
ACM Transactions on Computation Theory (TOCT)     Hybrid Journal   (Followers: 12)
ACM Transactions on Computational Logic (TOCL)     Hybrid Journal   (Followers: 3)
ACM Transactions on Computer Systems (TOCS)     Hybrid Journal   (Followers: 17)
ACM Transactions on Computer-Human Interaction     Hybrid Journal   (Followers: 14)
ACM Transactions on Computing Education (TOCE)     Hybrid Journal   (Followers: 5)
ACM Transactions on Design Automation of Electronic Systems (TODAES)     Hybrid Journal   (Followers: 3)
ACM Transactions on Economics and Computation     Hybrid Journal  
ACM Transactions on Embedded Computing Systems (TECS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Information Systems (TOIS)     Hybrid Journal   (Followers: 19)
ACM Transactions on Intelligent Systems and Technology (TIST)     Hybrid Journal   (Followers: 7)
ACM Transactions on Interactive Intelligent Systems (TiiS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)     Hybrid Journal   (Followers: 9)
ACM Transactions on Reconfigurable Technology and Systems (TRETS)     Hybrid Journal   (Followers: 6)
ACM Transactions on Sensor Networks (TOSN)     Hybrid Journal   (Followers: 7)
ACM Transactions on Speech and Language Processing (TSLP)     Hybrid Journal   (Followers: 8)
ACM Transactions on Storage     Hybrid Journal  
ACS Applied Materials & Interfaces     Full-text available via subscription   (Followers: 27)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 2)
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Ad Hoc Networks     Hybrid Journal   (Followers: 11)
Adaptive Behavior     Hybrid Journal   (Followers: 11)
Advanced Engineering Materials     Hybrid Journal   (Followers: 28)
Advanced Science Letters     Full-text available via subscription   (Followers: 9)
Advances in Adaptive Data Analysis     Hybrid Journal   (Followers: 7)
Advances in Artificial Intelligence     Open Access   (Followers: 15)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 18)
Advances in Computer Science : an International Journal     Open Access   (Followers: 15)
Advances in Computing     Open Access   (Followers: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 51)
Advances in Engineering Software     Hybrid Journal   (Followers: 27)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 13)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 23)
Advances in Human-Computer Interaction     Open Access   (Followers: 19)
Advances in Materials Sciences     Open Access   (Followers: 14)
Advances in Operations Research     Open Access   (Followers: 12)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 6)
Advances in Porous Media     Full-text available via subscription   (Followers: 5)
Advances in Remote Sensing     Open Access   (Followers: 43)
Advances in Science and Research (ASR)     Open Access   (Followers: 4)
Advances in Technology Innovation     Open Access   (Followers: 5)
AEU - International Journal of Electronics and Communications     Hybrid Journal   (Followers: 8)
African Journal of Information and Communication     Open Access   (Followers: 6)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 4)
AI EDAM     Hybrid Journal  
Air, Soil & Water Research     Open Access   (Followers: 11)
AIS Transactions on Human-Computer Interaction     Open Access   (Followers: 5)
Algebras and Representation Theory     Hybrid Journal   (Followers: 1)
Algorithms     Open Access   (Followers: 11)
American Journal of Computational and Applied Mathematics     Open Access   (Followers: 5)
American Journal of Computational Mathematics     Open Access   (Followers: 4)
American Journal of Information Systems     Open Access   (Followers: 5)
American Journal of Sensor Technology     Open Access   (Followers: 4)
Anais da Academia Brasileira de Ciências     Open Access   (Followers: 2)
Analog Integrated Circuits and Signal Processing     Hybrid Journal   (Followers: 7)
Analysis in Theory and Applications     Hybrid Journal   (Followers: 1)
Animation Practice, Process & Production     Hybrid Journal   (Followers: 5)
Annals of Combinatorics     Hybrid Journal   (Followers: 3)
Annals of Data Science     Hybrid Journal   (Followers: 11)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 12)
Annals of Pure and Applied Logic     Open Access   (Followers: 2)
Annals of Software Engineering     Hybrid Journal   (Followers: 13)
Annual Reviews in Control     Hybrid Journal   (Followers: 6)
Anuario Americanista Europeo     Open Access  
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applied and Computational Harmonic Analysis     Full-text available via subscription   (Followers: 1)
Applied Artificial Intelligence: An International Journal     Hybrid Journal   (Followers: 13)
Applied Categorical Structures     Hybrid Journal   (Followers: 2)
Applied Clinical Informatics     Hybrid Journal   (Followers: 2)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 11)
Applied Computer Systems     Open Access   (Followers: 2)
Applied Informatics     Open Access  
Applied Mathematics and Computation     Hybrid Journal   (Followers: 33)
Applied Medical Informatics     Open Access   (Followers: 10)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Soft Computing     Hybrid Journal   (Followers: 16)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 4)
Applied System Innovation     Open Access  
Architectural Theory Review     Hybrid Journal   (Followers: 3)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 5)
Archive of Numerical Software     Open Access  
Archives and Museum Informatics     Hybrid Journal   (Followers: 132)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 5)
arq: Architectural Research Quarterly     Hybrid Journal   (Followers: 7)
Artifact     Hybrid Journal   (Followers: 2)
Artificial Life     Hybrid Journal   (Followers: 7)
Asia Pacific Journal on Computational Engineering     Open Access  
Asia-Pacific Journal of Information Technology and Multimedia     Open Access   (Followers: 1)
Asian Journal of Computer Science and Information Technology     Open Access  
Asian Journal of Control     Hybrid Journal  
Assembly Automation     Hybrid Journal   (Followers: 2)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
Australian Educational Computing     Open Access   (Followers: 1)
Automatic Control and Computer Sciences     Hybrid Journal   (Followers: 4)
Automatic Documentation and Mathematical Linguistics     Hybrid Journal   (Followers: 5)
Automatica     Hybrid Journal   (Followers: 11)
Automation in Construction     Hybrid Journal   (Followers: 6)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 9)
Basin Research     Hybrid Journal   (Followers: 5)
Behaviour & Information Technology     Hybrid Journal   (Followers: 52)
Big Data and Cognitive Computing     Open Access   (Followers: 2)
Biodiversity Information Science and Standards     Open Access  
Bioinformatics     Hybrid Journal   (Followers: 283)
Biomedical Engineering     Hybrid Journal   (Followers: 15)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 13)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 19)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 35)
Briefings in Bioinformatics     Hybrid Journal   (Followers: 43)
British Journal of Educational Technology     Hybrid Journal   (Followers: 144)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 10)
c't Magazin fuer Computertechnik     Full-text available via subscription   (Followers: 1)
CALCOLO     Hybrid Journal  
Calphad     Hybrid Journal  
Canadian Journal of Electrical and Computer Engineering     Full-text available via subscription   (Followers: 14)
Capturing Intelligence     Full-text available via subscription  
Catalysis in Industry     Hybrid Journal   (Followers: 1)
CEAS Space Journal     Hybrid Journal   (Followers: 2)
Cell Communication and Signaling     Open Access   (Followers: 2)
Central European Journal of Computer Science     Hybrid Journal   (Followers: 5)
CERN IdeaSquare Journal of Experimental Innovation     Open Access   (Followers: 2)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chemometrics and Intelligent Laboratory Systems     Hybrid Journal   (Followers: 14)
ChemSusChem     Hybrid Journal   (Followers: 7)
China Communications     Full-text available via subscription   (Followers: 7)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
CIN Computers Informatics Nursing     Full-text available via subscription   (Followers: 11)
Circuits and Systems     Open Access   (Followers: 15)
Clean Air Journal     Full-text available via subscription   (Followers: 1)
CLEI Electronic Journal     Open Access  
Clin-Alert     Hybrid Journal   (Followers: 1)
Cluster Computing     Hybrid Journal   (Followers: 1)
Cognitive Computation     Hybrid Journal   (Followers: 4)
COMBINATORICA     Hybrid Journal  
Combinatorics, Probability and Computing     Hybrid Journal   (Followers: 4)
Combustion Theory and Modelling     Hybrid Journal   (Followers: 14)
Communication Methods and Measures     Hybrid Journal   (Followers: 12)
Communication Theory     Hybrid Journal   (Followers: 20)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications in Algebra     Hybrid Journal   (Followers: 3)
Communications in Computational Physics     Full-text available via subscription   (Followers: 2)
Communications in Partial Differential Equations     Hybrid Journal   (Followers: 3)
Communications of the ACM     Full-text available via subscription   (Followers: 52)
Communications of the Association for Information Systems     Open Access   (Followers: 16)
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering     Hybrid Journal   (Followers: 3)
Complex & Intelligent Systems     Open Access   (Followers: 1)
Complex Adaptive Systems Modeling     Open Access  
Complex Analysis and Operator Theory     Hybrid Journal   (Followers: 2)
Complexity     Hybrid Journal   (Followers: 6)
Complexus     Full-text available via subscription  
Composite Materials Series     Full-text available via subscription   (Followers: 8)
Computación y Sistemas     Open Access  
Computation     Open Access  
Computational and Applied Mathematics     Hybrid Journal   (Followers: 2)
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2)
Computational and Mathematical Organization Theory     Hybrid Journal   (Followers: 2)
Computational and Structural Biotechnology Journal     Open Access   (Followers: 2)
Computational and Theoretical Chemistry     Hybrid Journal   (Followers: 9)
Computational Astrophysics and Cosmology     Open Access   (Followers: 1)
Computational Biology and Chemistry     Hybrid Journal   (Followers: 11)
Computational Chemistry     Open Access   (Followers: 2)
Computational Cognitive Science     Open Access   (Followers: 2)
Computational Complexity     Hybrid Journal   (Followers: 4)
Computational Condensed Matter     Open Access  
Computational Ecology and Software     Open Access   (Followers: 9)
Computational Economics     Hybrid Journal   (Followers: 9)
Computational Geosciences     Hybrid Journal   (Followers: 15)
Computational Linguistics     Open Access   (Followers: 23)
Computational Management Science     Hybrid Journal  
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 8)
Computational Mechanics     Hybrid Journal   (Followers: 5)
Computational Methods and Function Theory     Hybrid Journal  
Computational Molecular Bioscience     Open Access   (Followers: 2)
Computational Optimization and Applications     Hybrid Journal   (Followers: 7)
Computational Particle Mechanics     Hybrid Journal   (Followers: 1)
Computational Research     Open Access   (Followers: 1)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computational Science and Techniques     Open Access  
Computational Statistics     Hybrid Journal   (Followers: 14)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 30)
Computer     Full-text available via subscription   (Followers: 94)
Computer Aided Surgery     Hybrid Journal   (Followers: 6)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 8)
Computer Communications     Hybrid Journal   (Followers: 10)
Computer Engineering and Applications Journal     Open Access   (Followers: 5)
Computer Journal     Hybrid Journal   (Followers: 9)
Computer Methods in Applied Mechanics and Engineering     Hybrid Journal   (Followers: 23)
Computer Methods in Biomechanics and Biomedical Engineering     Hybrid Journal   (Followers: 12)
Computer Methods in the Geosciences     Full-text available via subscription   (Followers: 2)
Computer Music Journal     Hybrid Journal   (Followers: 19)

        1 2 3 4 5 6 | Last

Journal Cover Biomedical Engineering, IEEE Transactions on
  [SJR: 1.201]   [H-I: 138]   [35 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0018-9294
   Published by IEEE Homepage  [191 journals]
  • Frontcover
    • Abstract: Presents the front cover for this issue of the publication.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • IEEE Engineering in Medicine and Biology Society
    • Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • IEEE Transactions on Biomedical Engineering (T-BME)
    • Abstract: Presents the publication's Statement of Editorial Policy.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • IEEE Transactions on Biomedical Engineering Handling Editors
    • Abstract: Presents a listing of the handling editors for this issue of the publication.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • Influence of Shoulder Kinematic Estimate on Joint and Muscle Mechanics
           Predicted by Musculoskeletal Model
    • Authors: Yoann Blache;Mickaël Begon;
      Pages: 715 - 722
      Abstract: Goal: Little information is available in the existing literature regarding the influence of the scapular kinematic estimate method on musculoskeletal analysis. This study aimed to assess the propagation of errors due to the method used for scapular kinematics reconstruction in the workflow of musculoskeletal modeling (joint kinematics, joint torques, muscle force, and joint reaction force) in shoulder and upper-limb movements. Methods: Two participants performed functional (arm elevation and rotation), daily life (eating and reaching pants pockets), and sports movements (a simulated throwing maneuver). Shoulder kinematics were obtained with five multibody kinematics methods: intracortical pins (Pins, reference method), International Society of Biomechanics (ISB), Jackson (Jack), Projection (Proj), and Ellipsoid (Ell) methods. For the five kinematics methods, joint torques, muscle forces, and glenohumeral joint reaction forces were computed with the Delft Shoulder and Elbow musculoskeletal model. Results: Differences up to 30° in glenohumeral joint kinematics, compared to the Pins method, resulted in differences less than 3 N.m in joint torque estimation. However, these also resulted in differences up to 50 and 831 N in the muscle force and joint reaction force estimate, respectively, in comparison to the reference method (Pins). No method yielded the worst or best results in comparison to the Pins method but the differences were task-specific. Conclusion: We concluded that shoulder biomechanical studies based on skin markers should be completed with caution when assessing joint angles, muscle forces, and glenohumeral joint reaction forces, while researchers may be more confident with the evaluation of shoulder joint torques.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • Arrhythmia Mechanism and Scaling Effect on the Spectral Properties of
           Electroanatomical Maps With Manifold Harmonics
    • Authors: Margarita Sanromán-Junquera;Inmaculada Mora-Jiménez;Arcadio García-Alberola;Antonio J. Caamaño;Beatriz Trenor;José L. Rojo-Álvarez;
      Pages: 723 - 732
      Abstract: Introduction: Spatial and temporal processing of intracardiac electrograms provides relevant information to support the arrhythmia ablation during electrophysiological studies. Current cardiac navigation systems (CNS) and electrocardiographic imaging (ECGI) build detailed 3-D electroanatomical maps (EAM), which represent the spatial anatomical distribution of bioelectrical features, such as activation time or voltage. Objective: We present a principled methodology for spectral analysis of both EAM geometry and bioelectrical feature in CNS or ECGI, including their spectral representation, cutoff frequency, or spatial sampling rate (SSR). Methods: Existing manifold harmonic techniques for spectral mesh analysis are adapted to account for a fourth dimension, corresponding to the EAM bioelectrical feature. Appropriate scaling is required to address different magnitudes and units. Results: With our approach, simulated and real EAM showed strong SSR dependence on both the arrhythmia mechanism and the cardiac anatomical shape. For instance, high frequencies increased significantly the SSR because of the “early-meets-late” in flutter EAM, compared with the sinus rhythm. Besides, higher frequency components were obtained for the left atrium (more complex anatomy) than for the right atrium in sinus rhythm. Conclusion: The proposed manifold harmonics methodology opens the field toward new signal processing tools for principled EAM spatiofeature analysis in CNS and ECGI, and to an improved knowledge on arrhythmia mechanisms.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • eCurves: A Temporal Shape Encoding
    • Authors: Elena Bernardis;Yong Zhang;Ender Konukoglu;Yangming Ou;Harold S. Javitz;Leon Axel;Dimitris Metaxas;Benoit Desjardins;Kilian M. Pohl;
      Pages: 733 - 744
      Abstract: Objective: This paper presents a framework for temporal shape analysis to capture the shape and changes of anatomical structures from three-dimensional+t(ime) medical scans. Method: We first encode the shape of a structure at each time point with the spectral signature, i.e., the eigenvalues and eigenfunctions of the Laplace operator. We then expand it to capture morphing shapes by tracking the eigenmodes across time according to the similarity of their eigenfunctions. The similarity metric is motivated by the fact that small-shaped deformations lead to minor changes in the eigenfunctions. Following each eigenmode from the beginning to end results in a set of eigenmode curves representing the shape and its changes over time. Results: We apply our encoding to a cardiac dataset consisting of series of segmentations outlining the right and left ventricles over time. We measure the accuracy of our encoding by training classifiers on discriminating healthy adults from patients that received reconstructive surgery for Tetralogy of Fallot (TOF). The classifiers based on our encoding significantly surpass deformation-based encodings of the right ventricle, the structure most impacted by TOF. Conclusion: The strength of our framework lies in its simplicity: It only assumes pose invariance within a time series but does not assume point-to-point correspondence across time series or a (statistical or physical) model. In addition, it is easy to implement and only depends on a single parameter, i.e., the number of curves.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • Electrocardiogram Signal Quality Assessment Based on Structural Image
           Similarity Metric
    • Authors: Yalda Shahriari;Richard Fidler;Michele M. Pelter;Yong Bai;Andrea Villaroman;Xiao Hu;
      Pages: 745 - 753
      Abstract: Objective: We developed an image-based electrocardiographic (ECG) quality assessment technique that mimics how clinicians annotate ECG signal quality. Methods: We adopted the structural similarity measure (SSIM) to compare images of two ECG records that are obtained from displaying ECGs in a standard scale. Then, a subset of representative ECG images from the training set was selected as templates through a clustering method. SSIM between each image and all the templates were used as the feature vector for the linear discriminant analysis classifier. We also employed three commonly used ECG signal quality index (SQI) measures: baseSQI, kSQI, and sSQI to compare with the proposed image quality index (IQI) approach. We used 1926 annotated ECGs, recorded from patient monitors, and associated with six different ECG arrhythmia alarm types which were obtained previously from an ECG alarm study at the University of California, San Francisco (UCSF). In addition, we applied the templates from the UCSF database to test the SSIM approach on the publicly available PhysioNet Challenge 2011 data. Results: For the UCSF database, the proposed IQI algorithm achieved an accuracy of 93.1% and outperformed all the SQI metrics, baseSQI, kSQI, and sSQI, with accuracies of 85.7%, 63.7%, and 73.8% respectively. Moreover, evaluation of our algorithm on the PhysioNet data showed an accuracy of 82.5%. Conclusion : The proposed algorithm showed better performance for assessing ECG signal quality than traditional signal processing methods. Significance: A more accurate assessment of ECG signal quality can lead to a more robust ECG-based diagnosis of cardiovascular conditions.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • A Novel Short-Term Event Extraction Algorithm for Biomedical Signals
    • Authors: Sasan Yazdani;Sibylle Fallet;Jean-Marc Vesin;
      Pages: 754 - 762
      Abstract: In this paper, we propose a fast novel nonlinear filtering method named Relative-Energy (Rel-En), for robust short-term event extraction from biomedical signals. We developed an algorithm that extracts short- and long-term energies in a signal and provides a coefficient vector with which the signal is multiplied, heightening events of interest. This algorithm is thoroughly assessed on benchmark datasets in three different biomedical applications, namely ECG QRS-complex detection, EEG K-complex detection, and imaging photoplethysmography (iPPG) peak detection. Rel-En successfully identified the events in these settings. Compared to the state-of-the-art, better or comparable results were obtained on QRS-complex and K-complex detection. For iPPG peak detection, the proposed method was used as a preprocessing step to a fixed threshold algorithm that lead to a significant improvement in overall results. While easily defined and computed, Rel-En robustly extracted short-term events of interest. The proposed algorithm can be implemented by two filters and its parameters can be selected easily and intuitively. Furthermore, Rel-En algorithm can be used in other biomedical signal processing applications where a need of short-term event extraction is present.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • Translational Motion Tracking of Leg Joints for Enhanced Prediction of
           Walking Tasks
    • Authors: Roman Stolyarov;Gary Burnett;Hugh Herr;
      Pages: 763 - 769
      Abstract: Objective: Walking task prediction in powered leg prostheses is an important problem in the development of biomimetic prosthesis controllers. This paper proposes a novel method to predict upcoming walking tasks by estimating the translational motion of leg joints using an integrated inertial measurement unit. Methods: We asked six subjects with unilateral transtibial amputations to traverse flat ground, ramps, and stairs using a powered prosthesis while inertial signals were collected. We then performed an offline analysis in which we simulated a real-time motion tracking algorithm on the inertial signals to estimate knee and ankle joint translations, and then used pattern recognition separately on the inertial and translational signal sets to predict the target walking tasks of individual strides. Results: Our analysis showed that using inertial signals to derive translational signals enabled a prediction error reduction of 6.8% compared to that attained using the original inertial signals. This result was similar to that seen by addition of surface electromyography sensors to integrated sensors in previous work, but was effected without adding any extra sensors. Finally, we reduced the size of the translational set to that of the inertial set and showed that the former still enabled a composite error reduction of 5.8%. Conclusion and Significance: These results indicate that translational motion tracking can be used to substantially enhance walking task prediction in leg prostheses without adding external sensing modalities. Our proposed algorithm can thus be used as a part of a task-adaptive and fully integrated prosthesis controller.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • Limb Position Tolerant Pattern Recognition for Myoelectric Prosthesis
           Control with Adaptive Sparse Representations From Extreme Learning
    • Authors: Joseph L. Betthauser;Christopher L. Hunt;Luke E. Osborn;Matthew R. Masters;György Lévay;Rahul R. Kaliki;Nitish V. Thakor;
      Pages: 770 - 778
      Abstract: Myoelectric signals can be used to predict the intended movements of an amputee for prosthesis control. However, untrained effects like limb position changes influence myoelectric signal characteristics, hindering the ability of pattern recognition algorithms to discriminate among motion classes. Despite frequent and long training sessions, these deleterious conditional influences may result in poor performance and device abandonment. Goal: We present a robust sparsity-based adaptive classification method that is significantly less sensitive to signal deviations resulting from untrained conditions. Methods: We compare this approach in the offline and online contexts of untrained upper-limb positions for amputee and able-bodied subjects to demonstrate its robustness compared against other myoelectric classification methods. Results: We report significant performance improvements (p
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • An In Vitro and Numerical Study of Moxibustion Therapy on Biological
    • Authors: Ying Li;Chao Sun;Jiujie Kuang;Changchun Ji;Shangsheng Feng;Jiangtao Wu;Haojun You;
      Pages: 779 - 788
      Abstract: Objective: Moxibustion therapy achieves satisfactory therapeutic effects largely depending on the heat stimulation of burning moxa. Understanding the thermal characteristics of heating process is an effective way to reveal the underlying mechanisms of moxibustion therapy. Methods: This paper performs experimental study on temperature distributions of burning moxa sticks and fresh in vitro porcine abdominal tissue using an infrared camera and thermocouples. Meanwhile, a moxibustion model incorporating moxa stick burning model and tissue heat transfer model was established with consideration of radiation propagation and water evaporation. Results: The burning features of moxa sticks were acquired and the radiation energy generated by the burning moxa stick was absorbed and scattered in biological tissue, resulting in a large temperature gradient in the skin layer. And the water evaporation led to a mass loss and reduced skin surface temperature. The numerical model was verified by experimental results and the effects of moxibustion treatment distance and duration can be quantified based on model calculation. Conclusion: The detailed heat transfer process of moxibustion was obtained experimentally and numerically. During moxibustion, the radiation attenuation and water evaporation have a significant influence on the energy transport in biological tissue which cannot be ignored. The treatment distance of 3 cm is the recommended value to achieve the treatment efficacy without thermal damage and pain. Significance: This research would reveal the underlying mechanisms of moxibustion therapy. Besides, the developed models are expected to establish a guideline for moxibustion clinical treatment.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • Turn Intent Detection For Control of a Lower Limb Prosthesis
    • Authors: Corey Pew;Glenn K. Klute;
      Pages: 789 - 796
      Abstract: Objective: An adaptable lower limb prosthesis with variable stiffness in the transverse plane requires a control method to effect changes in real time during amputee turning. This study aimed to identify classification algorithms that can accurately predict turning using inertial measurement unit (IMU) signals from the shank with adequate time to enact a change in stiffness during the swing phase of gait when the prosthesis is unloaded. Methods: To identify if a turning step is imminent, classification models were developed around activities of daily living including 90° spin turns, 90° step turns, 180° turns, and straight walking using simulated IMU data from the prosthesis shank. Three classifiers were tested: support vector machine (SVM), K nearest neighbors (KNN), and a bagged decision tree ensemble (Ensemble). Results: Individual training gave superior results over training on a pooled set of users. Coupled with a simple control scheme, the SVM, KNN, and Ensemble classifiers achieved 96%, 93%, and 91% accuracy (no significant difference), respectively, predicting an upcoming turn 400 ± 70 ms prior to the heel strike of the turn. However, classification of straight walking transition steps varied between classifiers at 85%, 82%, 97% (Ensemble significantly different, p = 0.002), respectively. Conclusion: The Ensemble model produced the best result overall; however, depending on the priority of identifying turning versus transition steps and processor performance, the SVM or KNN might still be considered. Significance: This research would be useful to help determine a classifier strategy for any lower limb device seeking to predict turn intent.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • A Novel Telemanipulated Robotic Assistant for Surgical Endoscopy:
           Preclinical Application to ESD
    • Authors: Lucile Zorn;Florent Nageotte;Philippe Zanne;Andras Legner;Bernard Dallemagne;Jacques Marescaux;Michel de Mathelin;
      Pages: 797 - 808
      Abstract: Objective: Minimally invasive surgical interventions in the gastrointestinal tract, such as endoscopic submucosal dissection (ESD), are very difficult for surgeons when performed with standard flexible endoscopes. Robotic flexible systems have been identified as a solution to improve manipulation. However, only a few such systems have been brought to preclinical trials as of now. As a result, novel robotic tools are required. Methods: We developed a telemanipulated robotic device, called STRAS, which aims to assist surgeons during intraluminal surgical endoscopy. This is a modular system, based on a flexible endoscope and flexible instruments, which provides 10 degrees of freedom (DoFs). The modularity allows the user to easily set up the robot and to navigate toward the operating area. The robot can then be teleoperated using master interfaces specifically designed to intuitively control all available DoFs. STRAS capabilities have been tested in laboratory conditions and during preclinical experiments. Results: We report 12 colorectal ESDs performed in pigs, in which large lesions were successfully removed. Dissection speeds are compared with those obtained in similar conditions with the manual Anubiscope platform from Karl Storz. We show significant improvements (p= 0.01). Conclusion: These experiments show that STRAS (v2) provides sufficient DoFs, workspace, and force to perform ESD, that it allows a single surgeon to perform all the surgical tasks and those performances are improved with respect to manual systems. Significance: The concepts developed for STRAS are validated and could bring new tools for surgeons to improve comfort, ease, and performances for intraluminal surgical endoscopy.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • Low Rank Enhanced Matrix Recovery of Hybrid Time and Frequency Data in
           Fast Magnetic Resonance Spectroscopy
    • Authors: Hengfa Lu;Xinlin Zhang;Tianyu Qiu;Jian Yang;Jiaxi Ying;Di Guo;Zhong Chen;Xiaobo Qu;
      Pages: 809 - 820
      Abstract: Goal: The two dimensional magnetic resonance spectroscopy (MRS) possesses many important applications in bioengineering but suffers from long acquisition duration. Non-uniform sampling has been applied to the spatiotemporally encoded ultrafast MRS, but results in missing data in the hybrid time and frequency plane. An approach is proposed to recover this missing signal, of which enables high quality spectrum reconstruction. M ethods: The natural exponential characteristic of MRS is exploited to recover the hybrid time and frequency signal. The reconstruction issue is formulated as a low rank enhanced Hankel matrix completion problem and is solved by a fast numerical algorithm. Results: Experiments on synthetic and real MRS data show that the proposed method provides faithful spectrum reconstruction, and outperforms the state-of-the-art compressed sensing approach on recovering low-intensity spectral peaks and robustness to different sampling patterns. C onclusion: The exponential signal property serves as an useful tool to model the time-domain MRS signals and even allows missing data recovery. The proposed method has been shown to reconstruct high quality MRS spectra from non-uniformly sampled data in the hybrid time and frequency plane. Significance: Low-intensity signal reconstruction is generally challenging in biological MRS and we provide a solution to this problem. The proposed method may be extended to recover signals that generally can be modeled as a sum of exponential functions in biomedical engineering applications, e.g., signal enhancement, feature extraction, and fast sampling.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • Minimizing the Translation Error in the Application of an Oblique
           Single-Cut Rotation Osteotomy: Where to Cut'
    • Authors: Johannes G. G. Dobbe;Simon D. Strackee;Geert J. Streekstra;
      Pages: 821 - 827
      Abstract: Objective: An oblique single cut rotation osteotomy enables correcting angular bone alignment in the coronal, sagittal, and transverse planes, with just a single oblique osteotomy, and by rotating one bone segment in the osteotomy plane. However, translational malalignment is likely to exist if the bone is curved or deformed and the location of the oblique osteotomy is not obvious. Methods: In this paper, we investigate how translational malalignment depends on the osteotomy location. We further propose and evaluate by simulation in 3-D, a method that minimizes translational malalignment by varying the osteotomy location and by sliding the distal bone segment with respect to the proximal bone segment within the oblique osteotomy plane. The method is finally compared to what three surgeons achieve by manually selecting the osteotomy location in 3-D virtual space without planning in-plane translations. Results: The minimization method optimized for length better than the surgeons did, by 3.2 mm on average, range (0.1, 9.4) mm, in 82% of the cases. A better translation in the axial plane was achieved by 4.1 mm on average, range (0.3, 14.4) mm, in 77% of the cases. Conclusion: The proposed method generally performs better than subjectively choosing an osteotomy position along the bone axis. Significance: The proposed method is considered a valuable tool for future alignment planning of an oblique single-cut rotation osteotomy since it helps minimizing translational malalignment.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • Orbit Segmentation by Surface Reconstruction With Automatic Sliced Vertex
    • Authors: Tai-Chiu Hsung;John Lo;Mei-Man Chong;Tazuko K. Goto;Lim-Kwong Cheung;
      Pages: 828 - 838
      Abstract: Goal: The purpose of this paper is to develop a computational approach to the segmentation of human orbits. Methods: The first step is to perform Hounsfield units thresholding to segment the bony structure around the orbit. Then, a three-dimensional mesh model is generated. Poisson surface reconstruction is applied to a set of automatically screened vertices, which are facing the inner orbital walls. These procedures effectively close orbital fissures; various nerves foramina; and interpolate the broken surfaces due to thin bone structures around the orbit. We also developed validation models with five dried skulls, where the orbits were filled with dental impression. Validations on the proposed algorithm were performed with the corresponding CT images and verified by experienced radiographer. Results: The mean volume differences are less than 0.3%. Surface differences are within 0.3 mm of root mean square. Both differences are not clinically significant. Significance: Traditional approaches are slice-by-slice manual editing or shape interpolation with selected slices interactively. It is not only time consuming, but also inefficient, exhibits interoperator variability, and repeatability problems. In the proposed method, most of the manual processes are eliminated with adjustable vertex screening parameters. It makes the proposed method repeatable.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • A Fiber Bragg Grating Sensor for Radial Artery Pulse Waveform Measurement
    • Authors: Dagong Jia;Jing Chao;Shuai Li;Hongxia Zhang;Yingzhan Yan;Tiegen Liu;Ye Sun;
      Pages: 839 - 846
      Abstract: In this paper, we report the design and experimental validation of a novel optical sensor for radial artery pulse measurement based on fiber Bragg grating (FBG) and lever amplification mechanism. Pulse waveform analysis is a diagnostic tool for clinical examination and disease diagnosis. High fidelity radial artery pulse waveform has been investigated in clinical studies for estimating central aortic pressure, which is proved to be predictors of cardiovascular diseases. As a three-dimensional cylinder, the radial artery needs to be examined from different locations to achieve optimal pulse waveform for estimation and diagnosis. The proposed optical sensing system is featured as high sensitivity and immunity to electromagnetic interference for multilocation radial artery pulse waveform measurement. The FBG sensor can achieve the sensitivity of 8.236 nm/N, which is comparable to a commonly used electrical sensor. This FBG-based system can provide high accurate measurement, and the key characteristic parameters can be then extracted from the raw signals for clinical applications. The detecting performance is validated through experiments guided by physicians. In the experimental validation, we applied this sensor to measure the pulse waveforms at various positions and depths of the radial artery in the wrist according to the diagnostic requirements. The results demonstrate the high feasibility of using optical systems for physiological measurement and using this FBG sensor for radial artery pulse waveform in clinical applications.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • Passive Wearable Skin Patch Sensor Measures Limb Hemodynamics Based on
           Electromagnetic Resonance
    • Authors: Kim Cluff;Ryan Becker;Balakumar Jayakumar;Kiyun Han;Ernie Condon;Kenneth Dudley;George Szatkowski;Iraklis I. Pipinos;Ryan Z. Amick;Jeremy Patterson;
      Pages: 847 - 856
      Abstract: Objective: The objectives of this study were to design and develop an open-circuit electromagnetic resonant skin patch sensor, characterize the fluid volume and resonant frequency relationship, and investigate the sensor's ability to measure limb hemodynamics and pulse volume waveform features. Methods: The skin patch was designed from an open-circuit electromagnetic resonant sensor comprised of a single baseline trace of copper configured into a square planar spiral which had a self-resonating response when excited by an external radio frequency sweep. Using a human arm phantom with a realistic vascular network, the sensor's performance to measure limb hemodynamics was evaluated. Results: The sensor was able to measure pulsatile blood flow which registered as shifts in the sensor's resonant frequencies. The time-varying waveform pattern of the resonant frequency displayed a systolic upstroke, a systolic peak, a dicrotic notch, and a diastolic down stroke. The resonant frequency waveform features and peak systolic time were validated against ultrasound pulse wave Doppler. A statistical correlation analysis revealed a strong correlation (R2 = 0.99) between the resonant sensor peak systolic time and the pulse wave Doppler peak systolic time. Conclusion: The sensor was able to detect pulsatile flow, identify hemodynamic waveform features, and measure heart rate with 98% accuracy. Significance: The open-circuit resonant sensor design leverages the architecture of a thin planar spiral which is passive (does not require batteries), robust and lightweight (does not have electrical components or electrical connections), and may be able to wirelessly monitor cardiovascular health and limb hemodynamics.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • GriFT: A Device for Quantifying Physiological and Pathological Mirror
           Movements in Children
    • Authors: Ellen Jaspers;Katrijn Klingels;Cristina Simon-Martinez;Hilde Feys;Daniel Graham Woolley;Nicole Wenderoth;
      Pages: 857 - 865
      Abstract: Goal: Mirror movements (MM) occur during unilateral actions and manifest as involuntary muscle activity of the passive limb, “mirroring” voluntary actions executed by the contralateral homologous body part. They are a normal motor feature in young children that gradually disappears. In children suffering from neurological disorders, e.g., unilateral cerebral palsy, MMs have been proposed to yield relevant information for diagnosis and therapy. However, in clinical practice, MM are typically assessed using an ordinal rating scale. Here, we introduce the grip force tracking (GriFT) device, a portable system to quantitatively assess MM during repetitive unimanual squeezing while playing a computer game. Methods: The GriFT device consists of two handles, each equipped with two compressive force sensors (range 0-23 kg, Fz 1000 Hz). Children complete three trials of unimanual squeezing, whereby the visual display on the screen determines the squeezing rhythm (0.67 Hz at 15% maximum voluntary contraction, force-level adjusted per hand). MMs are characterized based on frequency, amplitude, and temporal features (synchronization, timing). Results: MM differed significantly between children with different clinical MM scores. MM frequency and amplitude were most discriminative. Categorization of physiological MM proved highly sensitive (89%-97%). Conclusion: We demonstrated feasibility and validity of the GriFT device in a large cohort of typically developing children (N = 174, age 5-15 years), and its clinical applicability in children with unilateral cerebral palsy with various levels of hand function. Significance: The quantification of MM is a promising tool to further investigate and categorize MM in children with unilateral cerebral palsy.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • Sequential Therapeutic Response Modeling for Tumor Treatment Using
           Computational Hybrid Control Systems Approach
    • Authors: Wasiu Opeyemi Oduola;Xiangfang L. Li;Chang Duan;Lijun Qian;Edward R. Dougherty;
      Pages: 866 - 874
      Abstract: Objective: Tumorigenesis is due to uncontrolled cell division arising from mutations and alterations in the proliferative controls of the cell population. The fight against tumor growth and development has often relied on combination therapy that has been acclaimed as one of the main standards of care in cancer therapeutics and prevention of drug-related resistances. The toxicity of the combinatorial drugs raises a significant concern whenever patients take two or more drugs concurrently at the maximum tolerated dose. A promising solution in tumor treatment involves the administration of the drugs in an alternating or sequential fashion rather than a simultaneous manner. In this paper, we investigate how feasible such an approach is from a mathematical perspective and propose a switched hybrid control systems framework. Methods: We explore the response of tumor cells dynamics to sequential drugs administration with the aid of a time-dependent switching strategy. A transit compartmentalized model is employed to describe the tumor cells progression to death. Results: The design of the time-based drug switching logic ensures the proliferating tumor cells are repressed. Conclusions: Simulation results are provided using the tumor growth dynamics with sequential drugs intake to demonstrate the effectiveness of the proposed method in reducing the tumor size. Significance: This paper is the first attempt to provide a switched hybrid control systems framework on sequential drug administration to biomedical researchers and clinicians.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • Dedicated Entropy Measures for Early Assessment of Pregnancy Progression
           From Single-Channel Electrohysterography
    • Authors: Massimo Mischi;Chuan Chen;Tanya Ignatenko;Hinke de Lau;Beijing Ding;S. G. Guid Oei;Chiara Rabotti;
      Pages: 875 - 884
      Abstract: Objective: Preterm birth is a large-scale clinical problem involving over 10% of infants. Diagnostic means for timely risk assessment are lacking and the underlying physiological mechanisms unclear. To improve the evaluation of pregnancy before term, we introduce dedicated entropy measures derived from a single-channel electrohysterogram (EHG). Methods: The estimation of approximate entropy (ApEn) and sample entropy (SampEn) is adjusted to monitor variations in the regularity of single-channel EHG recordings, reflecting myoelectrical changes due to pregnancy progression. In particular, modifications in the tolerance metrics are introduced for improving robustness to EHG amplitude fluctuations. An extensive database of 58 EHG recordings with 4 monopolar channels in women presenting with preterm contractions was manually annotated and used for validation. The methods were tested for their ability to recognize the onset of labor and the risk of preterm birth. Comparison with the best single-channel methods according to the literature was performed. Results: The reference methods were outperformed. SampEn and ApEn produced the best prediction of delivery, although only one channel showed a significant difference ($p
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • An Ambulatory Gait Monitoring System with Activity Classification and Gait
           Parameter Calculation Based on a Single Foot Inertial Sensor
    • Authors: Minsu Song;Jonghyun Kim;
      Pages: 885 - 893
      Abstract: Goal: For healthcare and clinical use, ambulatory gait monitoring systems using inertial sensors have been developed to estimate the user gait parameters, such as walking speed, stride time, and stride length. However, to adapt the systems effectively to daily-life activities, they need to be able to classify the gait activities of daily-life to obtain the parameters for each activity. In this study, we propose a simple classification algorithm based on a single inertial sensor for ease of use, which classifies three major gait activities: leveled walk, ramp walk, and stair walk. Method: The classification can be performed with gait parameter estimation simultaneously. The developed system that includes classification and parameter estimation algorithms was evaluated with eight healthy subjects within a gait lab and on an outdoor daily-life walking course. Results: The results showed that the estimated gait parameters were comparable to existing studies (range of walking speed root mean square error: 0.059-0.129 m/s), and the classification accuracy was sufficiently high for all three gait activities: 98.5% for the indoor gait lab experiment and 95.5% for the outdoor complex daily-life walking course experiment. Conclusion: The proposed system is simple and effective for daily-life gait analysis, including gait activity classification and gait parameter estimation for each activity.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • Optimal Mixed Tracking/Impedance Control With Application to Transfemoral
           Prostheses With Energy Regeneration
    • Authors: Gholamreza Khademi;Hanieh Mohammadi;Hanz Richter;Dan Simon;
      Pages: 894 - 910
      Abstract: Objective: We design an optimal passivity-based tracking/impedance control system for a robotic manipulator with energy regenerative electronics, where the manipulator has both actively and semi-actively controlled joints. The semi-active joints are driven by a regenerative actuator that includes an energy-storing element. Method: External forces can have a large influence on energy regeneration characteristics. Impedance control is used to impose a desired relationship between external forces and deviation from reference trajectories. Multi-objective optimization (MOO) is used to obtain optimal impedance parameters and control gains to compromise between the two conflicting objectives of trajectory tracking and energy regeneration. We solve the MOO problem under two different scenarios: 1) constant impedance; and 2) time-varying impedance. Results: The methods are applied to a transfemoral prosthesis simulation with a semi-active knee joint. Normalized hypervolume and relative coverage are used to compare Pareto fronts, and these two metrics show that time-varying impedance provides better performance than constant impedance. The solution with time-varying impedance with minimum tracking error (0.0008 rad) fails to regenerate energy (loses 9.53 J), while a solution with degradation in tracking (0.0452 rad) regenerates energy (gains 270.3 J). A tradeoff solution results in fair tracking (0.0178 rad) and fair energy regeneration (131.2 J). Conclusion: Our experimental results support the possibility of net energy regeneration at the semi-active knee joint with human-like tracking performance. Significance: The results indicate that advanced control and optimization of ultracapacitor-based systems can significantly reduce power requirements in transfemoral prostheses.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • Spiral Gradient Coil Design for Use in Cylindrical MRI Systems
    • Authors: Yaohui Wang;Xuegang Xin;Feng Liu;Stuart Crozier;
      Pages: 911 - 920
      Abstract: In magnetic resonance imaging, the stream function based method is commonly used in the design of gradient coils. However, this method can be prone to errors associated with the discretization of continuous current density and wire connections. In this paper, we propose a novel gradient coil design scheme that works directly in the wire space, avoiding the system errors that may appear in the stream function approaches. Specifically, the gradient coil pattern is described with dedicated spiral functions adjusted to allow the coil to produce the required field gradients in the imaging area, minimal stray field, and other engineering terms. The performance of a designed spiral gradient coil was compared with its stream-function counterpart. The numerical evaluation shows that when compared with the conventional solution, the inductance and resistance was reduced by 20.9 and 10.5%, respectively. The overall coil performance (evaluated by the figure of merit (FoM)) was improved up to 26.5% for the x -gradient coil design; for the z-gradient coil design, the inductance and resistance were reduced by 15.1 and 6.7% respectively, and the FoM was increased by 17.7%. In addition, by directly controlling the wire distributions, the spiral gradient coil design was much sparser than conventional coils.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • Broadband Vibration Detection in Tissue Phantoms Using a Fiber
           Fabry–Perot Cavity
    • Authors: Jack Barnes;Sijia Li;Apoorv Goyal;Purang Abolmaesumi;Parvin Mousavi;Hans-Peter Loock;
      Pages: 921 - 927
      Abstract: Objective: A fiber optic vibration sensor is developed and characterized with an ultrawide dynamic sensing range, from less than 1 Hz to clinical ultrasound frequencies near 6 MHz. The vibration sensor consists of a matched pair of fiber Bragg gratings coupled to a custom-built signal processing circuit. The wavelength of a laser diode is locked to one of the many cavity resonances using the Pound-Drever-Hall scheme. Methods: A calibrated piezoelectric vibration element was used to characterize the sensor's strain, temperature, and noise responses. To demonstrate its sensing capability, an ultrasound phantom with built-in low frequency vibration actuation was constructed. Results: The fiber optic senor was shown to simultaneously capture the low frequency vibration and the clinical ultrasound transmission waveforms with nanostrain sensitivity. Conclusion: This miniaturized and sensitive vibration sensor can provide comprehensive information regarding strain response and the resultant ultrasound waveforms.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • Treatment of Cancer In Vitro Using Radiation and High-Frequency Bursts of
           Submicrosecond Electrical Pulses
    • Authors: Michael B. Sano;Olga Volotskova;Lei Xing;
      Pages: 928 - 935
      Abstract: High-frequency irreversible electroporation (H-FIRE) is an emerging cancer therapy, which uses bursts of short duration, alternating polarity, high-voltage electrical pulses to focally ablate tumors. Here, we present a preliminary investigation of the combinatorial effects of H-FIRE and ionizing radiation. In vitro cell cultures were exposed to bursts of 500 ns pulses and single radiation doses of 2 or 20 Gy then analyzed for 14 days. H-FIRE and radiation therapy (RT) appear to induce different delayed cell death mechanisms and in all treatment groups combinatorial therapy resulted in lower overall viabilities. These results indicate that in vivo investigation of the antitumor efficacy of combined H-FIRE and RT is warranted.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
  • Optimization-Based Image Reconstruction From Low-Count, List-Mode TOF-PET
    • Authors: Zheng Zhang;Sean Rose;Jinghan Ye;Amy E. Perkins;Buxin Chen;Chien-Min Kao;Emil Y. Sidky;Chi-Hua Tung;Xiaochuan Pan;
      Pages: 936 - 946
      Abstract: Objective: We investigate an optimization-based approach to image reconstruction from list-mode data in digital time-of-flight (TOF) positron emission tomography (PET) imaging. Method: In the study, the image to be reconstructed is designed as a solution to a convex, non-smooth optimization program, and a primal-dual algorithm is developed for image reconstruction by solving the optimization program. The algorithm is first applied to list-mode TOF-PET data of a typical count level from physical phantoms and a human subject. Subsequently, we explore the algorithm's potential for image reconstruction in low-dose and/or fast TOF-PET imaging of practical interest by applying the algorithm to list-mode TOF-PET data of different, low-count levels from the same physical phantoms and human subject. Results: Visual inspection and quantitative-metric analysis reveal that the optimization reconstruction approach investigated can yield images with enhanced spatial and contrast resolution, suppressed image noise, and increased axial volume coverage over the reference images obtained with a standard clinical reconstruction algorithm especially for low-dose TOF-PET data. Significance: The optimization-based reconstruction approach can be exploited for yielding insights into potential quality upper bound of reconstructed images in, and design of scanning protocols of, TOF-PET imaging of practical significance.
      PubDate: April 2018
      Issue No: Vol. 65, No. 4 (2018)
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
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Fax: +00 44 (0)131 4513327
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