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ENGINEERING (1330 journals)                  1 2 3 4 5 6 7 | Last

Showing 1 - 200 of 1205 Journals sorted alphabetically
3 Biotech     Open Access   (Followers: 8)
3D Research     Hybrid Journal   (Followers: 21)
AAPG Bulletin     Hybrid Journal   (Followers: 8)
AASRI Procedia     Open Access   (Followers: 15)
Abstract and Applied Analysis     Open Access   (Followers: 3)
Aceh International Journal of Science and Technology     Open Access   (Followers: 7)
ACS Nano     Hybrid Journal   (Followers: 322)
Acta Geotechnica     Hybrid Journal   (Followers: 7)
Acta Metallurgica Sinica (English Letters)     Hybrid Journal   (Followers: 7)
Acta Polytechnica : Journal of Advanced Engineering     Open Access   (Followers: 3)
Acta Scientiarum. Technology     Open Access   (Followers: 3)
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Active and Passive Electronic Components     Open Access   (Followers: 7)
Adaptive Behavior     Hybrid Journal   (Followers: 10)
Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi     Open Access  
Adsorption     Hybrid Journal   (Followers: 5)
Advanced Engineering Forum     Full-text available via subscription   (Followers: 9)
Advanced Journal of Graduate Research     Open Access  
Advanced Nonlinear Studies     Hybrid Journal  
Advanced Science     Open Access   (Followers: 6)
Advanced Science Focus     Free   (Followers: 5)
Advanced Science Letters     Full-text available via subscription   (Followers: 11)
Advanced Science, Engineering and Medicine     Partially Free   (Followers: 8)
Advanced Synthesis & Catalysis     Hybrid Journal   (Followers: 16)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 6)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Complex Systems     Hybrid Journal   (Followers: 10)
Advances in Engineering Software     Hybrid Journal   (Followers: 29)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 17)
Advances in Fuzzy Systems     Open Access   (Followers: 5)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 14)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 24)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 23)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 8)
Advances in Natural Sciences: Nanoscience and Nanotechnology     Open Access   (Followers: 29)
Advances in Nonlinear Analysis     Open Access  
Advances in Operations Research     Open Access   (Followers: 12)
Advances in OptoElectronics     Open Access   (Followers: 6)
Advances in Physics Theories and Applications     Open Access   (Followers: 16)
Advances in Polymer Science     Hybrid Journal   (Followers: 45)
Advances in Porous Media     Full-text available via subscription   (Followers: 5)
Advances in Remote Sensing     Open Access   (Followers: 51)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Aerobiologia     Hybrid Journal   (Followers: 3)
African Journal of Science, Technology, Innovation and Development     Hybrid Journal   (Followers: 6)
AIChE Journal     Hybrid Journal   (Followers: 35)
Ain Shams Engineering Journal     Open Access   (Followers: 5)
Akademik Platform Mühendislik ve Fen Bilimleri Dergisi     Open Access   (Followers: 1)
Al-Nahrain Journal for Engineering Sciences     Open Access  
Alexandria Engineering Journal     Open Access   (Followers: 1)
AMB Express     Open Access   (Followers: 1)
American Journal of Applied Sciences     Open Access   (Followers: 27)
American Journal of Engineering and Applied Sciences     Open Access   (Followers: 10)
American Journal of Engineering Education     Open Access   (Followers: 12)
American Journal of Environmental Engineering     Open Access   (Followers: 16)
American Journal of Industrial and Business Management     Open Access   (Followers: 25)
Anadolu University Journal of Science and Technology A : Applied Sciences and Engineering     Open Access  
Annals of Civil and Environmental Engineering     Open Access  
Annals of Combinatorics     Hybrid Journal   (Followers: 4)
Annals of Pure and Applied Logic     Open Access   (Followers: 4)
Annals of Regional Science     Hybrid Journal   (Followers: 8)
Annals of Science     Hybrid Journal   (Followers: 7)
Antarctic Science     Hybrid Journal   (Followers: 1)
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applicable Analysis: An International Journal     Hybrid Journal   (Followers: 1)
Applied Catalysis A: General     Hybrid Journal   (Followers: 7)
Applied Catalysis B: Environmental     Hybrid Journal   (Followers: 20)
Applied Clay Science     Hybrid Journal   (Followers: 6)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 14)
Applied Magnetic Resonance     Hybrid Journal   (Followers: 4)
Applied Nanoscience     Open Access   (Followers: 9)
Applied Network Science     Open Access   (Followers: 3)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Physics Research     Open Access   (Followers: 6)
Applied Sciences     Open Access   (Followers: 4)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 7)
Arab Journal of Basic and Applied Sciences     Open Access  
Arabian Journal for Science and Engineering     Hybrid Journal   (Followers: 5)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 6)
Archives of Foundry Engineering     Open Access  
Archives of Thermodynamics     Open Access   (Followers: 9)
Arid Zone Journal of Engineering, Technology and Environment     Open Access   (Followers: 2)
Arkiv för Matematik     Hybrid Journal   (Followers: 2)
ASEE Prism     Full-text available via subscription   (Followers: 3)
Asia-Pacific Journal of Science and Technology     Open Access  
Asian Engineering Review     Open Access  
Asian Journal of Applied Science and Engineering     Open Access   (Followers: 2)
Asian Journal of Applied Sciences     Open Access   (Followers: 2)
Asian Journal of Biotechnology     Open Access   (Followers: 9)
Asian Journal of Control     Hybrid Journal  
Asian Journal of Technology Innovation     Hybrid Journal   (Followers: 8)
Assembly Automation     Hybrid Journal   (Followers: 2)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
ATZagenda     Hybrid Journal  
ATZextra worldwide     Hybrid Journal  
AURUM : Mühendislik Sistemleri ve Mimarlık Dergisi = Aurum Journal of Engineering Systems and Architecture     Open Access  
Australasian Physical & Engineering Sciences in Medicine     Hybrid Journal   (Followers: 1)
Australian Journal of Multi-Disciplinary Engineering     Full-text available via subscription   (Followers: 2)
Autocracy : Jurnal Otomasi, Kendali, dan Aplikasi Industri     Open Access  
Automotive Experiences     Open Access  
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 8)
Avances en Ciencias e Ingeniería     Open Access  
Avances en Ciencias e Ingenierías     Open Access  
Balkan Region Conference on Engineering and Business Education     Open Access   (Followers: 1)
Bangladesh Journal of Scientific and Industrial Research     Open Access  
Basin Research     Hybrid Journal   (Followers: 5)
Batteries     Open Access   (Followers: 6)
Bautechnik     Hybrid Journal   (Followers: 2)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 28)
Beni-Suef University Journal of Basic and Applied Sciences     Open Access   (Followers: 4)
BER : Manufacturing Survey : Full Survey     Full-text available via subscription   (Followers: 1)
BER : Motor Trade Survey     Full-text available via subscription  
BER : Retail Sector Survey     Full-text available via subscription   (Followers: 1)
BER : Retail Survey : Full Survey     Full-text available via subscription   (Followers: 1)
BER : Survey of Business Conditions in Manufacturing : An Executive Summary     Full-text available via subscription   (Followers: 3)
BER : Survey of Business Conditions in Retail : An Executive Summary     Full-text available via subscription   (Followers: 3)
Beyond : Undergraduate Research Journal     Open Access  
Bhakti Persada : Jurnal Aplikasi IPTEKS     Open Access  
Bharatiya Vaigyanik evam Audyogik Anusandhan Patrika (BVAAP)     Open Access   (Followers: 1)
Bilge International Journal of Science and Technology Research     Open Access  
Biofuels Engineering     Open Access   (Followers: 1)
Biointerphases     Open Access   (Followers: 1)
Biomaterials Science     Full-text available via subscription   (Followers: 12)
Biomedical Engineering     Hybrid Journal   (Followers: 16)
Biomedical Engineering     Hybrid Journal   (Followers: 2)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 13)
Biomedical Engineering Letters     Hybrid Journal   (Followers: 5)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 19)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 35)
Biomedical Engineering: Applications, Basis and Communications     Hybrid Journal   (Followers: 5)
Biomedical Microdevices     Hybrid Journal   (Followers: 8)
Biomedical Science and Engineering     Open Access   (Followers: 4)
Biomicrofluidics     Open Access   (Followers: 5)
BioNanoMaterials     Open Access   (Followers: 2)
Biotechnology Progress     Hybrid Journal   (Followers: 40)
Bitlis Eren University Journal of Science and Technology     Open Access  
Black Sea Journal of Engineering and Science     Open Access  
Boletin Cientifico Tecnico INIMET     Open Access  
Botswana Journal of Technology     Full-text available via subscription   (Followers: 1)
Boundary Value Problems     Open Access   (Followers: 1)
Brazilian Journal of Science and Technology     Open Access   (Followers: 2)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 12)
Bulletin of Canadian Petroleum Geology     Full-text available via subscription   (Followers: 13)
Bulletin of Engineering Geology and the Environment     Hybrid Journal   (Followers: 14)
Bulletin of the Crimean Astrophysical Observatory     Hybrid Journal  
Cahiers Droit, Sciences & Technologies     Open Access  
Calphad     Hybrid Journal   (Followers: 2)
Canadian Geotechnical Journal     Hybrid Journal   (Followers: 32)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 44)
Carbon Resources Conversion     Open Access   (Followers: 1)
Case Studies in Engineering Failure Analysis     Open Access   (Followers: 6)
Case Studies in Thermal Engineering     Open Access   (Followers: 6)
Catalysis Communications     Hybrid Journal   (Followers: 6)
Catalysis Letters     Hybrid Journal   (Followers: 2)
Catalysis Reviews: Science and Engineering     Hybrid Journal   (Followers: 9)
Catalysis Science and Technology     Hybrid Journal   (Followers: 9)
Catalysis Surveys from Asia     Hybrid Journal   (Followers: 3)
Catalysis Today     Hybrid Journal   (Followers: 7)
CEAS Space Journal     Hybrid Journal   (Followers: 2)
Cellular and Molecular Neurobiology     Hybrid Journal   (Followers: 3)
Central European Journal of Engineering     Hybrid Journal  
Chaos : An Interdisciplinary Journal of Nonlinear Science     Hybrid Journal   (Followers: 3)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
Chinese Journal of Engineering     Open Access   (Followers: 2)
Chinese Science Bulletin     Open Access   (Followers: 1)
Ciencia e Ingenieria Neogranadina     Open Access  
Ciencia en su PC     Open Access   (Followers: 1)
Ciencia y Tecnología     Open Access  
Ciencias Holguin     Open Access   (Followers: 3)
CienciaUAT     Open Access   (Followers: 1)
Cientifica     Open Access  
CIRP Annals - Manufacturing Technology     Full-text available via subscription   (Followers: 11)
CIRP Journal of Manufacturing Science and Technology     Full-text available via subscription   (Followers: 13)
City, Culture and Society     Hybrid Journal   (Followers: 23)
Clean Air Journal     Full-text available via subscription   (Followers: 1)
Clinical Science     Hybrid Journal   (Followers: 8)
Coal Science and Technology     Full-text available via subscription   (Followers: 3)
Coastal Engineering     Hybrid Journal   (Followers: 11)
Coastal Engineering Journal     Hybrid Journal   (Followers: 6)
Coatings     Open Access   (Followers: 4)
Cogent Engineering     Open Access   (Followers: 3)
Cognitive Computation     Hybrid Journal   (Followers: 3)
Color Research & Application     Hybrid Journal   (Followers: 3)
COMBINATORICA     Hybrid Journal  
Combustion Theory and Modelling     Hybrid Journal   (Followers: 14)
Combustion, Explosion, and Shock Waves     Hybrid Journal   (Followers: 15)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering     Open Access  
Communications in Information Science and Management Engineering     Open Access   (Followers: 4)
Communications in Numerical Methods in Engineering     Hybrid Journal   (Followers: 2)
Components, Packaging and Manufacturing Technology, IEEE Transactions on     Hybrid Journal   (Followers: 29)
Composite Interfaces     Hybrid Journal   (Followers: 7)
Composite Structures     Hybrid Journal   (Followers: 294)
Composites Part A : Applied Science and Manufacturing     Hybrid Journal   (Followers: 236)
Composites Part B : Engineering     Hybrid Journal   (Followers: 273)
Composites Science and Technology     Hybrid Journal   (Followers: 207)
Comptes Rendus Mécanique     Full-text available via subscription   (Followers: 2)
Computation     Open Access   (Followers: 1)
Computational Geosciences     Hybrid Journal   (Followers: 17)

        1 2 3 4 5 6 7 | Last

Journal Cover
Biomedical Engineering Letters
Journal Prestige (SJR): 0.332
Citation Impact (citeScore): 1
Number of Followers: 5  
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 2093-9868 - ISSN (Online) 2093-985X
Published by Springer-Verlag Homepage  [2352 journals]
  • Multiscale self-quotient filtering for an improved unsupervised retinal
           blood vessels characterisation
    • Authors: D. Relan; R. Relan
      Pages: 59 - 68
      Abstract: Digital images often suffer from contrast variability and non-uniform illumination, which seriously affect the evaluation of biomarkers such as the arteriolar to venular ratio. This biomarker provides valuable information about many pathological conditions such as diabetes, hypertension etc. Hence, in order to efficiently estimate the biomarkers, correct classification of retinal vessels extracted from digital images, into arterioles and venules is an important research problem. This paper presents an unsupervised retinal vessel classification approach which utilises the multiscale self-quotient filtering, to pre-process the input image before extracting the discriminating features. Thereafter the squared-loss mutual information clustering method is used for the unsupervised classification of retinal vessels. The proposed vessel classification method was evaluated on the publicly available DRIVE and INSPIRE-AVR databases. The proposed unclassified framework resulted in 93.2 and 88.9% classification rate in zone B for the DRIVE and the INSPIRE-AVR dataset respectively. The proposed method outperformed other tested methods available in the literature. Retinal vessel classification, in an unsupervised setting is a challenging task. The present framework provided high classification rate and therefore holds a great potential to aid computer aided diagnosis and biomarker research.
      PubDate: 2018-02-01
      DOI: 10.1007/s13534-017-0040-5
      Issue No: Vol. 8, No. 1 (2018)
  • Automatic heart activity diagnosis based on Gram polynomials and
           probabilistic neural networks
    • Authors: Francesco Beritelli; Giacomo Capizzi; Grazia Lo Sciuto; Christian Napoli; Francesco Scaglione
      Pages: 77 - 85
      Abstract: The paper proposes a new approach to heart activity diagnosis based on Gram polynomials and probabilistic neural networks (PNN). Heart disease recognition is based on the analysis of phonocardiogram (PCG) digital sequences. The PNN provides a powerful tool for proper classification of the input data set. The novelty of the proposed approach lies in a powerful feature extraction based on Gram polynomials and the Fourier transform. The proposed system presents good performance obtaining overall sensitivity of 93%, specificity of 91% and accuracy of 94%, using a public database of over 3000 heart beat sound recordings, classified as normal and abnormal heart sounds. Thus, it can be concluded that Gram polynomials and PNN prove to be a very efficient technique using the PCG signal for characterizing heart diseases.
      PubDate: 2018-02-01
      DOI: 10.1007/s13534-017-0046-z
      Issue No: Vol. 8, No. 1 (2018)
  • The research of sleep staging based on single-lead electrocardiogram and
           deep neural network
    • Authors: Ran Wei; Xinghua Zhang; Jinhai Wang; Xin Dang
      Pages: 87 - 93
      Abstract: The polysomnogram (PSG) analysis is considered the golden standard for sleep staging under the clinical environment. The electroencephalogram (EEG) signal is the most important signal for classification of sleep stages. However, in-vivo signal recording and analysis of EEG signal presents us with a few technical challenges. Electrocardiogram signals on the other hand, are easier to record, and can provide an attractive alternative for home sleep monitoring. In this paper we describe a method based on deep neural network (DNN), which can be used for the classification of the sleep stages into Wake (W), rapid-eye-movement (REM) and non-rapid-eye-movement (NREM) sleep stage. We apply the sleep stage stacked autoencoder to constitute a 4-layer DNN model. In order to test the accuracy of our method, eighteen PSGs from the MIT-BIH Polysomnographic Database were used. A total of 11 features were extracted from each electrocardiogram recording The experimental design employs cross-validation across subjects, ensuring the independence of the training and the test data. We obtained an accuracy of 77% and a Cohen’s kappa coefficient of about 0.56 for the classification of Wake, REM and NREM.
      PubDate: 2018-02-01
      DOI: 10.1007/s13534-017-0044-1
      Issue No: Vol. 8, No. 1 (2018)
  • Electrodeless conductivity tensor imaging (CTI) using MRI: basic theory
           and animal experiments
    • Authors: Saurav Z. K. Sajib; Oh In Kwon; Hyung Joong Kim; Eung Je Woo
      Abstract: The electrical conductivity is a passive material property primarily determined by concentrations of charge carriers and their mobility. The macroscopic conductivity of a biological tissue at low frequency may exhibit anisotropy related with its structural directionality. When expressed as a tensor and properly quantified, the conductivity tensor can provide diagnostic information of numerous diseases. Imaging conductivity distributions inside the human body requires probing it by externally injecting conduction currents or inducing eddy currents. At low frequency, the Faraday induction is negligible and it has been necessary in most practical cases to inject currents through surface electrodes. Here we report a novel method to reconstruct conductivity tensor images using an MRI scanner without current injection. This electrodeless method of conductivity tensor imaging (CTI) utilizes B1 mapping to recover a high-frequency isotropic conductivity image which is influenced by contents in both extracellular and intracellular spaces. Multi-b diffusion weighted imaging is then utilized to extract the effects of the extracellular space and incorporate its directional structural property. Implementing the novel CTI method in a clinical MRI scanner, we reconstructed in vivo conductivity tensor images of canine brains. Depending on the details of the implementation, it may produce conductivity contrast images for conductivity weighted imaging (CWI). Clinical applications of CTI and CWI may include imaging of tumor, ischemia, inflammation, cirrhosis, and other diseases. CTI can provide patient-specific models for source imaging, transcranial dc stimulation, deep brain stimulation, and electroporation.
      PubDate: 2018-04-25
      DOI: 10.1007/s13534-018-0066-3
  • Photoacoustic microscopy: principles and biomedical applications
    • Authors: Wei Liu; Junjie Yao
      Abstract: Photoacoustic microscopy (PAM) has become an increasingly popular technology for biomedical applications, providing anatomical, functional, and molecular information. In this concise review, we first introduce the basic principles and typical system designs of PAM, including optical-resolution PAM and acoustic-resolution PAM. The major imaging characteristics of PAM, i.e. spatial resolutions, penetration depth, and scanning approach are discussed in detail. Then, we introduce the major biomedical applications of PAM, including anatomical imaging across scales from cellular level to organismal level, label-free functional imaging using endogenous biomolecules, and molecular imaging using exogenous contrast agents. Lastly, we discuss the technical and engineering challenges of PAM in the translation to potential clinical impacts.
      PubDate: 2018-04-25
      DOI: 10.1007/s13534-018-0067-2
  • Multimodal photoacoustic imaging as a tool for sentinel lymph node
           identification and biopsy guidance
    • Authors: Haemin Kim; Jin Ho Chang
      Abstract: As a minimally invasive method, sentinel lymph node biopsy (SLNB) in conjunction with guidance methods is the standard method to determine cancer metastasis in breast. The desired guidance methods for SLNB should be capable of precise SLN localization for accurate diagnosis of micro-metastases at an early stage of cancer progression and thus facilitate reducing the number of SLN biopsies for minimal surgical complications. For this, high sensitivity to the administered dyes, high spatial and contrast resolutions, deep imaging depth, and real-time imaging capability are pivotal requirements. Currently, various methods have been used for SLNB guidance, each with their own advantages and disadvantages, but no methods meet the requirements. In this review, we discuss the conventional SLNB guidance methods in this perspective. In addition, we focus on the role of the PA imaging modality on real-time SLN identification and biopsy guidance. In particular, PA-based hybrid imaging methods for precise SLN identification and efficient biopsy guidance are introduced, and their unique features, advantages, and disadvantages are discussed.
      PubDate: 2018-04-21
      DOI: 10.1007/s13534-018-0068-1
  • The application of ECG cancellation in diaphragmatic electromyographic by
           using stationary wavelet transform
    • Authors: Guo Luo; Zhi Yang
      Abstract: In this paper, we present and investigate a special kind of stationary wavelet algorithm using “inverse” hard threshold to eliminate the electrocardiogram (ECG) interference included in diaphragmatic electromyographic (EMGdi). Differing from traditional wavelet hard threshold, “inverse” hard threshold is used to shrink strong coefficients of ECG interference and reserve weak coefficients of EMGdi signal. Meanwhile, a novel QRS location algorithm is proposed for the position detection of R wave by using low frequency coefficients in this paper. With the proposed method, raw EMGdi is decomposed by wavelet at fifth scale. Then, each ECG interference threshold is calculated by mean square, which is estimated by wavelet coefficients in the ECG cycle at each level. Finally, ECG interference wavelet coefficients are removed by “inverse” hard threshold, and then the de-noised signal is reconstructed by wavelet coefficients. The simulation and clinical EMGdi de-noising results show that the “inverse” hard threshold investigated in this paper removes the ECG interference in EMGdi availably and reserves its signal characteristics effectively, as compared to wavelet threshold.
      PubDate: 2018-04-21
      DOI: 10.1007/s13534-018-0064-5
  • Surface morphology characterization of laser-induced titanium implants:
           lesson to enhance osseointegration process
    • Authors: Javad Tavakoli; Mohammad E. Khosroshahi
      Abstract: The surface properties of implant are responsible to provide mechanical stability by creating an intimate bond between the bone and implant; hence, play a major role on osseointegration process. The current study was aimed to measure surface characteristics of titanium modified by a pulsed Nd:YAG laser. The results of this study revealed an optimum density of laser energy (140 Jcm−2), at which improvement of osteointegration process was seen. Significant differences were found between arithmetical mean height (Ra), root mean square deviation (Rq) and texture orientation, all were lower for 140 Jcm−2 samples compared to untreated one. Also it was identified that the surface segments were more uniformly distributed with a more Gaussian distribution for treated samples at 140 Jcm−2. The distribution of texture orientation at high laser density (250 and 300 Jcm−2) were approximately similar to untreated sample. The skewness index that indicates how peaks and valleys are distributed throughout the surface showed a positive value for laser treated samples, compared to untreated one. The surface characterization revealed that Kurtosis index, which tells us how high or flat the surface profile is, for treated sample at 140 Jcm−2 was marginally close to 3 indicating flat peaks and valleys in the surface profile.
      PubDate: 2018-04-04
      DOI: 10.1007/s13534-018-0063-6
  • Mechanical properties and cytotoxicity of PLA/PCL films
    • Authors: Heeseok Jeong; Jeongwon Rho; Ji-Yeon Shin; Deuk Yong Lee; Taeseon Hwang; Kwang J. Kim
      Abstract: Thermodynamically immiscible poly(lactic acid) (PLA) and poly(ε-caprolactone) (PCL) were blended and solution-cast by adding the 3% compatibilizer (tributyl citrate, TBC) of the PCL weight. In the PLA/PCL composition range of 99/1–95/5 wt%, mechanical properties of the PLA/PCL films with TBC were always superior to those of the films without TBC. The tensile strength of 42.9 ± 3.5 MPa and the elongation at break of 10.3 ± 2.7% were observed for the 93/7 PLA/PCL films without TBC, indicating that PCL addition is effective for strength and ductility. However, the tensile strength of 54.1 ± 3.4 MPa and the elongation at break of 8.8 ± 1.8% were found for the 95/5 PLA/PCL with TBC, indicating that the effect of co-addition of PCL and TBC on mechanical properties of the films is more pronounced. No cytotoxicity was observed for the PLA/PCL films regardless of TBC addition.
      PubDate: 2018-04-04
      DOI: 10.1007/s13534-018-0065-4
  • Clinical photoacoustic imaging platforms
    • Authors: Wonseok Choi; Eun-Yeong Park; Seungwan Jeon; Chulhong Kim
      Abstract: Photoacoustic imaging (PAI) is a new promising medical imaging technology available for diagnosing and assessing various pathologies. PAI complements existing imaging modalities by providing information not currently available for diagnosing, e.g., oxygenation level of the underlying tissue. Currently, researchers are translating PAI from benchside to bedside to make unique clinical advantages of PAI available for patient care. The requirements for a successful clinical PAI system are; deeper imaging depth, wider field of view, and faster scan time than the laboratory-level PAI systems. Currently, many research groups and companies are developing novel technologies for data acquisition/signal processing systems, detector geometry, and an acoustic sensor. In this review, we summarize state-of-the-art clinical PAI systems with three types of the imaging transducers: linear array transducer, curved linear array transducer, and volumetric array transducer. We will also discuss the limitations of the current PAI systems and describe latest techniques being developed to address these for further enhancing the image quality of PAI for successful clinical translation.
      PubDate: 2018-04-04
      DOI: 10.1007/s13534-018-0062-7
  • Multimodal intravascular photoacoustic and ultrasound imaging
    • Authors: Yan Li; Zhongping Chen
      Abstract: The rupture of atherosclerotic plaques is the leading cause of death in developed countries. Early identification of vulnerable plaque is the essential step in preventing acute coronary events. Intravascular photoacoustic (IVPA) technology is able to visualize chemical composition of atherosclerotic plaque with high specificity and sensitivity. Integrated with intravascular ultrasound (IVUS) imaging, this multimodal intravascular IVPA/IVUS imaging technology is able to provide both structural and chemical compositions of arterial walls for detecting and characterizing atherosclerotic plaques. In this paper, we present representative multimodal IVPA/IVUS imaging systems and discuss current scientific innovations, potential limitations, and prospective improvements for characterization of coronary atherosclerosis.
      PubDate: 2018-03-26
      DOI: 10.1007/s13534-018-0061-8
  • Naphthalocyanines as contrast agents for photoacoustic and multimodal
    • Authors: Upendra Chitgupi; Jonathan F. Lovell
      Abstract: Naphthalocyanines (Ncs) are a family of aromatic small molecule with large near infrared extinction coefficients, making them appealing contrast agent candidates for photoacoustic imaging (PAI). Depending on the substitutions on the Nc periphery or metal center, different spectrally-resolved absorption peak wavelengths are possible, which can enable photoacoustic contrast multiplexing. Owing to their generally poor aqueous solubility, approaches have been developed to modify Ncs or formulate them as biocompatible contrast agents for PAI. Due to their inherent capacity for metal ion chelation, Ncs hold potential for complementary multimodal contrast imaging techniques such as 64Cu positron emission tomography. In this research perspective, we highlight some recent reports involving the use of Ncs in PAI.
      PubDate: 2018-03-07
      DOI: 10.1007/s13534-018-0059-2
  • Fast photoacoustic imaging systems using pulsed laser diodes: a review
    • Authors: Paul Kumar Upputuri; Manojit Pramanik
      Abstract: Photoacoustic imaging (PAI) is a newly emerging imaging modality for preclinical and clinical applications. The conventional PAI systems use Q-switched Nd:YAG/OPO (Optical Parametric Oscillator) nanosecond lasers as excitation sources. Such lasers are expensive, bulky, and imaging speed is limited because of low pulse repetition rate. In recent years, the semiconductor laser technology has advanced to generate high-repetitions rate near-infrared pulsed lasers diodes (PLDs) which are reliable, less-expensive, hand-held, and light-weight, about 200 g. In this article, we review the development and demonstration of PLD based PAI systems for preclinical and clinical applications reported in recent years.
      PubDate: 2018-03-06
      DOI: 10.1007/s13534-018-0060-9
  • Machine learning in biomedical engineering
    • Authors: Cheolsoo Park; Clive Cheong Took; Joon-Kyung Seong
      PubDate: 2018-02-06
      DOI: 10.1007/s13534-018-0058-3
  • Obstructive sleep apnoea detection using convolutional neural network
           based deep learning framework
    • Authors: Debangshu Dey; Sayanti Chaudhuri; Sugata Munshi
      Abstract: This letter presents an automated obstructive sleep apnoea (OSA) detection method with high accuracy, based on a deep learning framework employing convolutional neural network. The proposed work develops a system that takes single lead electrocardiography signals from patients for analysis and detects the OSA condition of the patient. The results show that the proposed method has some advantages in solving such problems and it outperforms the existing methods significantly. The present scheme eliminates the requirement of separate feature extraction and classification algorithms for the detection of OSA. The proposed network performs both feature learning and classifies the features in a supervised manner. The scheme is computation-intensive, but can achieve very high degree of accuracy—on an average a margin of more than 9% compared to other published literature till date. The method also has a good immunity to the contamination of the signals by noise. Even with pessimistic signal to noise ratio values considered here, the methods already reported are not able to outshine the present method. The software for the algorithm reported here can be a good contender to constitute a module that can be integrated with a portable medical diagnostic system.
      PubDate: 2017-12-14
      DOI: 10.1007/s13534-017-0055-y
  • A computational model of ureteral peristalsis and an investigation into
           ureteral reflux
    • Authors: G. Hosseini; C. Ji; D. Xu; M. A. Rezaienia; E. Avital; A. Munjiza; J. J. R. Williams; J. S. A. Green
      Abstract: The aim of this study is to create a computational model of the human ureteral system that accurately replicates the peristaltic movement of the ureter for a variety of physiological and pathological functions. The objectives of this research are met using our in-house fluid-structural dynamics code (CgLes–Y code). A realistic peristaltic motion of the ureter is modelled using a novel piecewise linear force model. The urodynamic responses are investigated under two conditions of a healthy and a depressed contraction force. A ureteral pressure during the contraction shows a very good agreement with corresponding clinical data. The results also show a dependency of the wall shear stresses on the contraction velocity and it confirms the presence of a high shear stress at the proximal part of the ureter. Additionally, it is shown that an inefficient lumen contraction can increase the possibility of a continuous reflux during the propagation of peristalsis.
      PubDate: 2017-11-18
      DOI: 10.1007/s13534-017-0053-0
  • Elastography for portable ultrasound
    • Authors: Bonghun Shin; Soo Jeon; Jeongwon Ryu; Hyock Ju Kwon
      Abstract: Portable wireless ultrasound has been emerging as a new ultrasound device due to its unique advantages including small size, lightweight, wireless connectivity and affordability. Modern portable ultrasound devices can offer high quality sonogram images and even multiple ultrasound modes such as color Doppler, echocardiography, and endovaginal examination. However, none of them can provide elastography function yet due to the limitations in computational performance and data transfer speed of wireless communication. Also phase-based strain estimator (PSE) that is commonly used for conventional elastography cannot be adopted for portable ultrasound, because ultrasound parameters such as data dumping interval are varied significantly in the practice of portable ultrasound. Therefore, this research aims to propose a new elastography method suitable for portable ultrasound, called the robust phase-based strain estimator (RPSE), which is not only robust to the variation of ultrasound parameters but also computationally effective. Performance and suitability of RPSE were compared with other strain estimators including time-delay, displacement-gradient and phase-based strain estimators (TSE, DSE and PSE, respectively). Three types of raw RF data sets were used for validation tests: two numerical phantom data sets modeled by an open ultrasonic simulation code (Field II) and a commercial FEA (Abaqus), and the one experimentally acquired with a portable ultrasound device from a gelatin phantom. To assess image quality of elastograms, signal-to-noise (SNRe) and contrast-to-noise (CNRe) ratios were measured on the elastograms produced by each strain estimator. The computational efficiency was also estimated and compared. Results from the numerical phantom experiment showed that RPSE could achieve highest values of SNRe and CNRe (around 5.22 and 47.62 dB) among all strain estimators tested, and almost 10 times higher computational efficiency than TSE and DSE (around 0.06 vs. 5.76 s per frame for RPSE and TSE, respectively).
      PubDate: 2017-10-27
      DOI: 10.1007/s13534-017-0052-1
  • Performance of machine learning methods in diagnosing Parkinson’s
           disease based on dysphonia measures
    • Authors: Salim Lahmiri; Debra Ann Dawson; Amir Shmuel
      Abstract: Parkinson’s disease (PD) is a widespread degenerative syndrome that affects the nervous system. Its early appearing symptoms include tremor, rigidity, and vocal impairment (dysphonia). Consequently, speech indicators are important in the identification of PD based on dysphonic signs. In this regard, computer-aided-diagnosis systems based on machine learning can be useful in assisting clinicians in identifying PD patients. In this work, we evaluate the performance of machine learning based techniques for PD diagnosis based on dysphonia symptoms. Several machine learning techniques were considered and trained with a set of twenty-two voice disorder measurements to classify healthy and PD patients. These machine learning methods included linear discriminant analysis (LDA), k nearest-neighbors (k-NN), naïve Bayes (NB), regression trees (RT), radial basis function neural networks (RBFNN), support vector machine (SVM), and Mahalanobis distance classifier. We evaluated the performance of these methods by means of a tenfold cross validation protocol. Experimental results show that the SVM classifier achieved higher average performance than all other classifiers in terms of overall accuracy, G-mean, and area under the curve of the receiver operating characteristic plot. The SVM classifier achieved higher performance measures than the majority of the other classifiers also in terms of sensitivity, specificity, and F-measure statistics. The LDA, k-NN and RT achieved the highest average precision. The RBFNN method yielded the highest F-measure.; however, it performed poorly in terms of other performance metrics. Finally, t tests were performed to evaluate statistical significance of the results, confirming that the SVM outperformed most of the other classifiers on the majority of performance measures. SVM is a promising method for identifying PD patients based on classification of dysphonia measurements.
      PubDate: 2017-10-12
      DOI: 10.1007/s13534-017-0051-2
  • Computer-assisted brain tumor type discrimination using magnetic resonance
           imaging features
    • Authors: Sajid Iqbal; M. Usman Ghani Khan; Tanzila Saba; Amjad Rehman
      Abstract: Medical imaging plays an integral role in the identification, segmentation, and classification of brain tumors. The invention of MRI has opened new horizons for brain-related research. Recently, researchers have shifted their focus towards applying digital image processing techniques to extract, analyze and categorize brain tumors from MRI. Categorization of brain tumors is defined in a hierarchical way moving from major to minor ones. A plethora of work could be seen in literature related to the classification of brain tumors in categories such as benign and malignant. However, there are only a few works reported on the multiclass classification of brain images where each part of the image containing tumor is tagged with major and minor categories. The precise classification is difficult to achieve due to ambiguities in images and overlapping characteristics of different type of tumors. In the current study, a comprehensive review of recent research on brain tumors multiclass classification using MRI is provided. These multiclass classification studies are categorized into two major groups: XX and YY and each group are further divided into three sub-groups. A set of common parameters from the reviewed works is extracted and compared to highlight the merits and demerits of individual works. Based on our analysis, we provide a set of recommendations for researchers and professionals working in the area of brain tumors classification.
      PubDate: 2017-10-04
      DOI: 10.1007/s13534-017-0050-3
  • Gastrointestinal polyp detection in endoscopic images using an improved
           feature extraction method
    • Authors: Mustain Billah; Sajjad Waheed
      Abstract: Gastrointestinal polyps are treated as the precursors of cancer development. So, possibility of cancers can be reduced at a great extent by early detection and removal of polyps. The most used diagnostic modality for gastrointestinal polyps is video endoscopy. But, as an operator dependant procedure, several human factors can lead to miss detection of polyps. In this peper, an improved computer aided polyp detection method has been proposed. Proposed improved method can reduce polyp miss detection rate and assists doctors in finding the most important regions to pay attention. Color wavelet features and convolutional neural network features are extracted from endoscopic images, which are used for training a support vector machine. Then a target endoscopic image will be given to the classifier as input in order to find whether it contains any polyp or not. If polyp is found, it will be marked automatically. Experiment shows that, color wavelet features and convolutional neural network features together construct a highly representative of endoscopic polyp images. Evaluations on standard public databases show that, proposed system outperforms state-of-the-art methods, gaining accuracy of 98.34%, sensitivity of 98.67% and specificity of 98.23%. In this paper, the strength of color wavelet features and power of convolutional neural network features are combined. Fusion of these two methodology and use of support vector machine results in an improved method for gastrointestinal polyp detection. An analysis of ROC reveals that, proposed method can be used for polyp detection purposes with greater accuracy than state-of-the-art methods.
      PubDate: 2017-09-07
      DOI: 10.1007/s13534-017-0048-x
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