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ENGINEERING (1326 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: 317)
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: 4)
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: 7)
Advanced Synthesis & Catalysis     Hybrid Journal   (Followers: 17)
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: 28)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 16)
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     Hybrid Journal  
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 Combinatorics     Hybrid Journal   (Followers: 4)
Annals of Pure and Applied Logic     Open Access   (Followers: 3)
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: 8)
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)
Automotive Experiences     Open Access  
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 8)
Avances en Ciencias e Ingeniería     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: 8)
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: 293)
Composites Part A : Applied Science and Manufacturing     Hybrid Journal   (Followers: 230)
Composites Part B : Engineering     Hybrid Journal   (Followers: 271)
Composites Science and Technology     Hybrid Journal   (Followers: 204)
Comptes Rendus Mécanique     Full-text available via subscription   (Followers: 2)
Computation     Open Access   (Followers: 1)
Computational Geosciences     Hybrid Journal   (Followers: 17)
Computational Optimization and Applications     Hybrid Journal   (Followers: 8)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 8)

        1 2 3 4 5 6 7 | Last

Journal Cover
Australasian Physical & Engineering Sciences in Medicine
Journal Prestige (SJR): 0.336
Citation Impact (citeScore): 1
Number of Followers: 1  
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0158-9938 - ISSN (Online) 1879-5447
Published by Springer-Verlag Homepage  [2352 journals]
  • Nonlinear analysis of electrodermal activity signals for healthy subjects
           and patients with chronic obstructive pulmonary disease
    • Authors: Serife Gokce Caliskan; Mehmet Dincer Bilgin; Mehmet Polatli
      Abstract: It is known that signals recorded from physiological systems represent nonlinear features. Several recent studies report that quantitative information about signal complexity is obtained by using nonlinear analysis algorithms. Chronic obstructive pulmonary disease (COPD) is one of the causes of mortality worldwide with an increasing prevalence. This study aims to investigate nonlinear parameters such as largest Lyapunov exponent (LLE) and correlation dimension of electrodermal activity signals recorded from healthy subjects and patients with COPD. Electrodermal activity signals recorded from 14 healthy subjects and 24 patients with COPD were analysed. Auditory and tactile stimuli were applied at different time intervals during the recording process. Signals were reconstructed in the phase space compatible with theory and LLE and correlation dimension values were calculated. Statistical analysis was performed by using Shapiro–Wilk normality test, one-way analysis of variance (ANOVA) with Bonferroni post-test and Kruskal–Wallis non-parametric test. It was determined that the chaoticity and the complexity of the system increased in the presence of COPD. The systematic auditory stimuli increases chaoticity more than random auditory stimuli. Furthermore it was observed that participants develop habituation to the same auditory stimuli in time. There is no significant difference between COPD groups. Different results were found for the tactile stimuli applied to right or left ear. The results revealed that the nonlinear analysis of physiological data can be used for the development of new strategies for the diagnosis of chronic diseases.
      PubDate: 2018-06-01
      DOI: 10.1007/s13246-018-0649-4
  • The effect of work system on the hand exposure of workers in 18 F-FDG
           production centres
    • Authors: Małgorzata Wrzesień
      Abstract: The production of the 18F isotope—the marker of deoxyglucose (18F-FDG)—the radiopharmaceutical most commonly used in the oncological diagnostic technique of positron emission tomography, requires a cyclotron device. At present, there are nine facilities working in Poland that are equipped with cyclotrons used for producing the short-lived isotopes. The aim of the paper is to determine the hand exposure of workers employed in the two 18F-FDG production centres taking in to account the production procedures and work system in those facilities. Measurements, which included all professional workers exposed to ionizing radiation that were employed in two facilities, were performed by using high-sensitivity thermoluminescent detectors during the routine activities of the personnel. The work system used at the production centre has an impact on the level of the recorded doses. Among the production procedures performed by the staff, the highest ionizing radiation doses have been received by the staff during the 18F-FDG quality control. The maximum estimated annual Hp(0.07) for chemists from the quality control department can exceed the annual skin limit dose (500 mSv). The source of lowest doses on the hands are the cyclotron operating procedure and the 18F-FDG production, provided that these procedures can’t be combined with other production procedures.
      PubDate: 2018-06-01
      DOI: 10.1007/s13246-018-0644-9
  • Study on the dose modification factor of strut adjusted volume implant
           (SAVI) with a 169 Yb source using MCNP4C
    • Authors: Seyed Milad Vahabi; Mostean Bahreinipour; Mojtaba Shamsaie Zafarghandi
      Abstract: The SAVI has gained widespread use for accelerated partial breast irradiation (APBI) brachytherapy. Treatments with SAVI produce inherent heterogeneities including variable backscatter due to proximity to the tissue-air interface and variable cavity contents, causing inaccuracy in the dose calculation. In this study, a model of SAVI with sources of 169Yb developed recently was defined and simulations with MCNP4C code of Monte Carlo were performed through different scenarios to assess the effects of these heterogeneities on the dose distribution. The results showed that the dose delivered to target volume may be lower than the planned dose by up to 9–16%. Therefore, the therapy with169Yb must be viewed with caution and a correction factor must be applied in treatment planning systems. It was also observed that the presence of air cavity changed the relative dose 1% for a symmetric plan compared to a water cavity and up to 5% for an asymmetric plan. It was indicated that the dose modification factor (DMF) did not differ in any significant way to that of the symmetric plan. The effect of the composition on the DMF was negligible because the natures of water and breast tissue were approximately similar. All the obtained results indicated that should 169Yb sources be used with SAVI applications, some amendments of treatment planning systems would be employed.
      PubDate: 2018-06-01
      DOI: 10.1007/s13246-018-0641-z
  • Computed tomography imaging with the Adaptive Statistical Iterative
           Reconstruction (ASIR) algorithm: dependence of image quality on the
           blending level of reconstruction
    • Authors: Patrizio Barca; Marco Giannelli; Maria Evelina Fantacci; Davide Caramella
      Abstract: Computed tomography (CT) is a useful and widely employed imaging technique, which represents the largest source of population exposure to ionizing radiation in industrialized countries. Adaptive Statistical Iterative Reconstruction (ASIR) is an iterative reconstruction algorithm with the potential to allow reduction of radiation exposure while preserving diagnostic information. The aim of this phantom study was to assess the performance of ASIR, in terms of a number of image quality indices, when different reconstruction blending levels are employed. CT images of the Catphan-504 phantom were reconstructed using conventional filtered back-projection (FBP) and ASIR with reconstruction blending levels of 20, 40, 60, 80, and 100%. Noise, noise power spectrum (NPS), contrast-to-noise ratio (CNR) and modulation transfer function (MTF) were estimated for different scanning parameters and contrast objects. Noise decreased and CNR increased non-linearly up to 50 and 100%, respectively, with increasing blending level of reconstruction. Also, ASIR has proven to modify the NPS curve shape. The MTF of ASIR reconstructed images depended on tube load/contrast and decreased with increasing blending level of reconstruction. In particular, for low radiation exposure and low contrast acquisitions, ASIR showed lower performance than FBP, in terms of spatial resolution for all blending levels of reconstruction. CT image quality varies substantially with the blending level of reconstruction. ASIR has the potential to reduce noise whilst maintaining diagnostic information in low radiation exposure CT imaging. Given the opposite variation of CNR and spatial resolution with the blending level of reconstruction, it is recommended to use an optimal value of this parameter for each specific clinical application.
      PubDate: 2018-06-01
      DOI: 10.1007/s13246-018-0645-8
  • Drivers of change
    • Authors: Lisa Wilfert
      PubDate: 2018-06-01
      DOI: 10.1007/s13246-018-0648-5
  • Identification of a feature selection based pattern recognition scheme for
           finger movement recognition from multichannel EMG signals
    • Authors: Geethanjali Purushothaman; Raunak Vikas
      Abstract: This paper focuses on identification of an effective pattern recognition scheme with the least number of time domain features for dexterous control of prosthetic hand to recognize the various finger movements from surface electromyogram (EMG) signals. Eight channels EMG from 8 able-bodied subjects for 15 individuals and combined finger activities have been considered in this work. In this work, an attempt has been made to recognize a number of classes with the least number of features. Therefore, EMG signals are pre-processed using dual tree complex wavelet transform to improve the discriminating capability of features and time domain features such as zero crossing, slope sign change, mean absolute value, and waveform length is extracted from the pre-processed data. The performance of extracted features is studied with different classifiers such as linear discriminant analysis, naive Bayes classifier, quadratic support vector machine and cubic support vector machine with and without feature selection algorithms. The feature selection has been studied using particle swarm optimization (PSO) and ant colony optimization (ACO) with different number of features to identify the effect of features. The results demonstrated that naive Bayes classifier with ant colony optimization shows an average classification accuracy of 88.89% with a response time of 0.058025 ms for recognizing the 15 different finger movements with 16 features with significant difference in accuracy compared to SVM classifier with feature selection for a significance level of 0.05. There is no significant difference in the accuracy, specificity and sensitivity of an SVM classifier with and without feature selection. But the processing time is significantly more than the LDA and NB classifier. The PSO and ACO results revealed that slope sign changes contribute to recognizing the activity. In PSO, mean absolute value has been found to be effective compared to waveform length, contradictory with ACO. Further, the zero crossings have been found to be not effective in classification of finger movements in both the methods.
      PubDate: 2018-06-01
      DOI: 10.1007/s13246-018-0646-7
  • Classifying dysmorphic syndromes by using artificial neural network based
           hierarchical decision tree
    • Authors: Merve Erkınay Özdemir; Ziya Telatar; Osman Eroğul; Yusuf Tunca
      Abstract: Dysmorphic syndromes have different facial malformations. These malformations are significant to an early diagnosis of dysmorphic syndromes and contain distinctive information for face recognition. In this study we define the certain features of each syndrome by considering facial malformations and classify Fragile X, Hurler, Prader Willi, Down, Wolf Hirschhorn syndromes and healthy groups automatically. The reference points are marked on the face images and ratios between the points’ distances are taken into consideration as features. We suggest a neural network based hierarchical decision tree structure in order to classify the syndrome types. We also implement k-nearest neighbor (k-NN) and artificial neural network (ANN) classifiers to compare classification accuracy with our hierarchical decision tree. The classification accuracy is 50, 73 and 86.7% with k-NN, ANN and hierarchical decision tree methods, respectively. Then, the same images are shown to a clinical expert who achieve a recognition rate of 46.7%. We develop an efficient system to recognize different syndrome types automatically in a simple, non-invasive imaging data, which is independent from the patient’s age, sex and race at high accuracy. The promising results indicate that our method can be used for pre-diagnosis of the dysmorphic syndromes by clinical experts.
      PubDate: 2018-06-01
      DOI: 10.1007/s13246-018-0643-x
  • Multi-layer cube sampling for liver boundary detection in PET–CT
    • Authors: Xinxin Liu; Jian Yang; Shuang Song; Hong Song; Danni Ai; Jianjun Zhu; Yurong Jiang; Yongtian Wang
      Abstract: Liver metabolic information is considered as a crucial diagnostic marker for the diagnosis of fever of unknown origin, and liver recognition is the basis of automatic diagnosis of metabolic information extraction. However, the poor quality of PET and CT images is a challenge for information extraction and target recognition in PET–CT images. The existing detection method cannot meet the requirement of liver recognition in PET–CT images, which is the key problem in the big data analysis of PET–CT images. A novel texture feature descriptor called multi-layer cube sampling (MLCS) is developed for liver boundary detection in low-dose CT and PET images. The cube sampling feature is proposed for extracting more texture information, which uses a bi-centric voxel strategy. Neighbour voxels are divided into three regions by the centre voxel and the reference voxel in the histogram, and the voxel distribution information is statistically classified as texture feature. Multi-layer texture features are also used to improve the ability and adaptability of target recognition in volume data. The proposed feature is tested on the PET and CT images for liver boundary detection. For the liver in the volume data, mean detection rate (DR) and mean error rate (ER) reached 95.15 and 7.81% in low-quality PET images, and 83.10 and 21.08% in low-contrast CT images. The experimental results demonstrated that the proposed method is effective and robust for liver boundary detection.
      PubDate: 2018-06-01
      DOI: 10.1007/s13246-018-0650-y
  • Dosimetric characterisation of the optically-stimulated luminescence
           dosimeter in cobalt-60 high dose rate brachytherapy system
    • Authors: M. Rejab; J. H. D. Wong; Z. Jamalludin; W. L. Jong; R. A. Malik; W. Z. Wan Ishak; N. M. Ung
      Abstract: This study investigates the characteristics and application of the optically-stimulated luminescence dosimeter (OSLD) in cobalt-60 high dose rate (HDR) brachytherapy, and compares the results with the dosage produced by the treatment planning system (TPS). The OSLD characteristics comprised linearity, reproducibility, angular dependence, depth dependence, signal depletion, bleaching rate and cumulative dose measurement. A phantom verification exercise was also conducted using the Farmer ionisation chamber and in vivo diodes. The OSLD signal indicated a supralinear response (R2 = 0.9998). It exhibited a depth-independent trend after a steep dose gradient region. The signal depletion per readout was negligible (0.02%), with expected deviation for angular dependence due to off-axis sensitive volume, ranging from 1 to 16%. The residual signal of the OSLDs after 1 day bleached was within 1.5%. The accumulated and bleached OSLD signals had a standard deviation of ± 0.78 and ± 0.18 Gy, respectively. The TPS was found to underestimate the measured doses with deviations of 5% in OSLD, 17% in the Farmer ionisation chamber, and 7 and 8% for bladder and rectal diode probes. Discrepancies can be due to the positional uncertainty in the high-dose gradient. This demonstrates a slight displacement of the organ at risk near the steep dose gradient region will result in a large dose uncertainty. This justifies the importance of in vivo measurements in cobalt-60 HDR brachytherapy.
      PubDate: 2018-06-01
      DOI: 10.1007/s13246-018-0647-6
  • Winning images from the Photography in Medical Physics (PiMP) competition
    • PubDate: 2018-04-23
      DOI: 10.1007/s13246-018-0639-6
  • Alexander fractional differential window filter for ECG denoising
    • Authors: Atul Kumar Verma; Indu Saini; Barjinder Singh Saini
      Abstract: The electrocardiogram (ECG) non-invasively monitors the electrical activities of the heart. During the process of recording and transmission, ECG signals are often corrupted by various types of noises. Minimizations of these noises facilitate accurate detection of various anomalies. In the present paper, Alexander fractional differential window (AFDW) filter is proposed for ECG signal denoising. The designed filter is based on the concept of generalized Alexander polynomial and the R–L differential equation of fractional calculus. This concept is utilized to formulate a window that acts as a forward filter. Thereafter, the backward filter is constructed by reversing the coefficients of the forward filter. The proposed AFDW filter is then obtained by averaging of the forward and backward filter coefficients. The performance of the designed AFDW filter is validated by adding the various type of noise to the original ECG signal obtained from MIT-BIH arrhythmia database. The two non-diagnostic measure, i.e., SNR, MSE, and one diagnostic measure, i.e., wavelet energy based diagnostic distortion (WEDD) have been employed for the quantitative evaluation of the designed filter. Extensive experimentations on all the 48-records of MIT-BIH arrhythmia database resulted in average SNR of 22.014 ± 3.806365, 14.703 ± 3.790275, 13.3183 ± 3.748230; average MSE of 0.001458 ± 0.00028, 0.0078 ± 0.000319, 0.01061 ± 0.000472; and average WEDD value of 0.020169 ± 0.01306, 0.1207 ± 0.061272, 0.1432 ± 0.073588, for ECG signal contaminated by the power line, random, and the white Gaussian noise respectively. A new metric named as morphological power preservation measure (MPPM) is also proposed that account for the power preservance (as indicated by PSD plots) and the QRS morphology. The proposed AFDW filter retained much of the original (clean) signal power without any significant morphological distortion as validated by MPPM measure that were 0.0126, 0.08493, and 0.10336 for the ECG signal corrupted by the different type of noises. The versatility of the proposed AFDW filter is also validated by its application on the ECG signal from MIT-BIH database corrupted by the combination of the noises as well as on the real noisy ECG signals are taken from MIT-BIH ID database. Furthermore, the comparative study has also been done between the proposed AFDW filter and existing state of the art denoising algorithms. The results clearly prove the supremacy of our proposed AFDW filter.
      PubDate: 2018-04-23
      DOI: 10.1007/s13246-018-0642-y
  • ECG-derived respiration based on iterated Hilbert transform and Hilbert
           vibration decomposition
    • Authors: Hemant Sharma; K. K. Sharma
      Abstract: Monitoring of the respiration using the electrocardiogram (ECG) is desirable for the simultaneous study of cardiac activities and the respiration in the aspects of comfort, mobility, and cost of the healthcare system. This paper proposes a new approach for deriving the respiration from single-lead ECG based on the iterated Hilbert transform (IHT) and the Hilbert vibration decomposition (HVD). The ECG signal is first decomposed into the multicomponent sinusoidal signals using the IHT technique. Afterward, the lower order amplitude components obtained from the IHT are filtered using the HVD to extract the respiration information. Experiments are performed on the Fantasia and Apnea-ECG datasets. The performance of the proposed ECG-derived respiration (EDR) approach is compared with the existing techniques including the principal component analysis (PCA), R-peak amplitudes (RPA), respiratory sinus arrhythmia (RSA), slopes of the QRS complex, and R-wave angle. The proposed technique showed the higher median values of correlation (first and third quartile) for both the Fantasia and Apnea-ECG datasets as 0.699 (0.55, 0.82) and 0.57 (0.40, 0.73), respectively. Also, the proposed algorithm provided the lowest values of the mean absolute error and the average percentage error computed from the EDR and reference (recorded) respiration signals for both the Fantasia and Apnea-ECG datasets as 1.27 and 9.3%, and 1.35 and 10.2%, respectively. In the experiments performed over different age group subjects of the Fantasia dataset, the proposed algorithm provided effective results in the younger population but outperformed the existing techniques in the case of elderly subjects. The proposed EDR technique has the advantages over existing techniques in terms of the better agreement in the respiratory rates and specifically, it reduces the need for an extra step required for the detection of fiducial points in the ECG for the estimation of respiration which makes the process effective and less-complex. The above performance results obtained from two different datasets validate that the proposed approach can be used for monitoring of the respiration using single-lead ECG.
      PubDate: 2018-04-17
      DOI: 10.1007/s13246-018-0640-0
  • Fully convolutional networks (FCNs)-based segmentation method for
           colorectal tumors on T2-weighted magnetic resonance images
    • Authors: Junming Jian; Fei Xiong; Wei Xia; Rui Zhang; Jinhui Gu; Xiaodong Wu; Xiaochun Meng; Xin Gao
      Abstract: Segmentation of colorectal tumors is the basis of preoperative prediction, staging, and therapeutic response evaluation. Due to the blurred boundary between lesions and normal colorectal tissue, it is hard to realize accurate segmentation. Routinely manual or semi-manual segmentation methods are extremely tedious, time-consuming, and highly operator-dependent. In the framework of FCNs, a segmentation method for colorectal tumor was presented. Normalization was applied to reduce the differences among images. Borrowing from transfer learning, VGG-16 was employed to extract features from normalized images. We conducted five side-output blocks from the last convolutional layer of each block of VGG-16 along the network, these side-output blocks can deep dive multiscale features, and produced corresponding predictions. Finally, all of the predictions from side-output blocks were fused to determine the final boundaries of the tumors. A quantitative comparison of 2772 colorectal tumor manual segmentation results from T2-weighted magnetic resonance images shows that the average Dice similarity coefficient, positive predictive value, specificity, sensitivity, Hammoude distance, and Hausdorff distance were 83.56, 82.67, 96.75, 87.85%, 0.2694, and 8.20, respectively. The proposed method is superior to U-net in colorectal tumor segmentation (P < 0.05). There is no difference between cross-entropy loss and Dice-based loss in colorectal tumor segmentation (P > 0.05). The results indicate that the introduction of FCNs contributed to accurate segmentation of colorectal tumors. This method has the potential to replace the present time-consuming and nonreproducible manual segmentation method.
      PubDate: 2018-04-13
      DOI: 10.1007/s13246-018-0636-9
  • A prospective case study of high boost, high frequency emphasis and
           two-way diffusion filters on MR images of glioblastoma multiforme
    • Authors: B. N. Anoop; Justin Joseph; J. Williams; J. Sivaraman Jayaraman; Ansa Maria Sebastian; Praveer Sihota
      Abstract: Glioblastoma multiforme (GBM) appears undifferentiated and non-enhancing on magnetic resonance (MR) imagery. As MRI does not offer adequate image quality to allow visual discrimination of the boundary between GBM focus and perifocal vasogenic edema, surgical and radiotherapy planning become difficult. The presence of noise in MR images influences the computation of radiation dosage and precludes the edge based segmentation schemes in automated software for radiation treatment planning. The performance of techniques meant for simultaneous denoising and sharpening, like high boost filters, high frequency emphasize filters and two-way anisotropic diffusion is sensitive to the selection of their operational parameters. Improper selection may cause overshoot and saturation artefacts or noisy grey level transitions can be left unsuppressed. This paper is a prospective case study of the performance of high boost filters, high frequency emphasize filters and two-way anisotropic diffusion on MR images of GBM, for their ability to suppress noise from homogeneous regions and to selectively sharpen the true morphological edges. An objective method for determining the optimum value of the operational parameters of these techniques is also demonstrated. Saturation Evaluation Index (SEI), Perceptual Sharpness Index (PSI), Edge Model based Blur Metric (EMBM), Sharpness of Ridges (SOR), Structural Similarity Index Metric (SSIM), Peak Signal to Noise Ratio (PSNR) and Noise Suppression Ratio (NSR) are the objective functions used. They account for overshoot and saturation artefacts, sharpness of the image, width of salient edges (haloes), susceptibility of edge quality to noise, feature preservation and degree of noise suppression. Two-way diffusion is found to be superior to others in all these respects. The SEI, PSI, EMBM, SOR, SSIM, PSNR and NSR exhibited by two-way diffusion are 0.0016 ± 0.0012, 0.2049 ± 0.0187, 0.0905 ± 0.0408, 2.64 × 1012 ± 1.6 × 1012, 0.9955 ± 0.0024, 38.214 ± 5.2145 and 0.3547 ± 0.0069, respectively.
      PubDate: 2018-04-13
      DOI: 10.1007/s13246-018-0638-7
  • Investigation of contrast-enhanced subtracted breast CT images with MAP-EM
           based on projection-based weighting imaging
    • Authors: Zhengdong Zhou; Shaolin Guan; Runchao Xin; Jianbo Li
      Abstract: Contrast-enhanced subtracted breast computer tomography (CESBCT) images acquired using energy-resolved photon counting detector can be helpful to enhance the visibility of breast tumors. In such technology, one challenge is the limited number of photons in each energy bin, thereby possibly leading to high noise in separate images from each energy bin, the projection-based weighted image, and the subtracted image. In conventional low-dose CT imaging, iterative image reconstruction provides a superior signal-to-noise compared with the filtered back projection (FBP) algorithm. In this paper, maximum a posteriori expectation maximization (MAP-EM) based on projection-based weighting imaging for reconstruction of CESBCT images acquired using an energy-resolving photon counting detector is proposed, and its performance was investigated in terms of contrast-to-noise ratio (CNR). The simulation study shows that MAP-EM based on projection-based weighting imaging can improve the CNR in CESBCT images by 117.7%–121.2% compared with FBP based on projection-based weighting imaging method. When compared with the energy-integrating imaging that uses the MAP-EM algorithm, projection-based weighting imaging that uses the MAP-EM algorithm can improve the CNR of CESBCT images by 10.5%–13.3%. In conclusion, MAP-EM based on projection-based weighting imaging shows significant improvement the CNR of the CESBCT image compared with FBP based on projection-based weighting imaging, and MAP-EM based on projection-based weighting imaging outperforms MAP-EM based on energy-integrating imaging for CESBCT imaging.
      PubDate: 2018-04-10
      DOI: 10.1007/s13246-018-0634-y
  • Study of continuous blood pressure estimation based on pulse transit time,
           heart rate and photoplethysmography-derived hemodynamic covariates
    • Authors: Jingjie Feng; Zhongyi Huang; Congcong Zhou; Xuesong Ye
      Abstract: It is widely recognized that pulse transit time (PTT) can track blood pressure (BP) over short periods of time, and hemodynamic covariates such as heart rate, stiffness index may also contribute to BP monitoring. In this paper, we derived a proportional relationship between BP and PPT−2 and proposed an improved method adopting hemodynamic covariates in addition to PTT for continuous BP estimation. We divided 28 subjects from the Multi-parameter Intelligent Monitoring for Intensive Care database into two groups (with/without cardiovascular diseases) and utilized a machine learning strategy based on regularized linear regression (RLR) to construct BP models with different covariates for corresponding groups. RLR was performed for individuals as the initial calibration, while recursive least square algorithm was employed for the re-calibration. The results showed that errors of BP estimation by our method stayed within the Association of Advancement of Medical Instrumentation limits (− 0.98 ± 6.00 mmHg @ SBP, 0.02 ± 4.98 mmHg @ DBP) when the calibration interval extended to 1200-beat cardiac cycles. In comparison with other two representative studies, Chen’s method kept accurate (0.32 ± 6.74 mmHg @ SBP, 0.94 ± 5.37 mmHg @ DBP) using a 400-beat calibration interval, while Poon’s failed (− 1.97 ± 10.59 mmHg @ SBP, 0.70 ± 4.10 mmHg @ DBP) when using a 200-beat calibration interval. With additional hemodynamic covariates utilized, our method improved the accuracy of PTT-based BP estimation, decreased the calibration frequency and had the potential for better continuous BP estimation.
      PubDate: 2018-04-09
      DOI: 10.1007/s13246-018-0637-8
  • Glossokinetic potential based tongue–machine interface for 1-D
    • Authors: Kutlucan Gorur; M. Recep Bozkurt; M. Serdar Bascil; Feyzullah Temurtas
      Abstract: The tongue is an aesthetically useful organ located in the oral cavity. It can move in complex ways with very little fatigue. Many studies on assistive technologies operated by tongue are called tongue–human computer interface or tongue–machine interface (TMI) for paralyzed individuals. However, many of them are obtrusive systems consisting of hardware such as sensors and magnetic tracer placed in the mouth and on the tongue. Hence these approaches could be annoying, aesthetically unappealing and unhygienic. In this study, we aimed to develop a natural and reliable tongue–machine interface using solely glossokinetic potentials via investigation of the success of machine learning algorithms for 1-D tongue-based control or communication on assistive technologies. Glossokinetic potential responses are generated by touching the buccal walls with the tip of the tongue. In this study, eight male and two female naive healthy subjects, aged 22–34 years, participated. Linear discriminant analysis, support vector machine, and the k-nearest neighbor were used as machine learning algorithms. Then the greatest success rate was achieved an accuracy of 99% for the best participant in support vector machine. This study may serve disabled people to control assistive devices in natural, unobtrusive, speedy and reliable manner. Moreover, it is expected that GKP-based TMI could be alternative control and communication channel for traditional electroencephalography (EEG)-based brain–computer interfaces which have significant inadequacies arisen from the EEG signals.
      PubDate: 2018-04-09
      DOI: 10.1007/s13246-018-0635-x
  • Monte Carlo simulations for dose enhancement in cancer treatment using
           bismuth oxide nanoparticles implanted in brain soft tissue
    • Authors: Eslam Taha; Fathi Djouider; Essam Banoqitah
      Abstract: The objective of this work is to study the dosimetric performances of bismuth oxide nanoparticles implanted in tumors in cancer radiotherapy. GEANT4 based Monte Carlo numerical simulations were performed to assess dose enhancement distributions in and around a 1 × 1 × 1 cm3 tumor implanted with different concentrations of bismuth oxide and irradiated with low energies 125I, 131Cs, and 103Pd radioactive sources. Dose contributions were considered from photoelectrons, Auger electrons, and characteristic X-rays. Our results show the dose enhancement increased with increasing both bismuth oxide concentration in the target and photon energy. A dose enhancement factor up to 18.55 was obtained for a concentration of 70 mg/g of bismuth oxide in the tumor when irradiated with 131Cs source. This study showed that bismuth oxide nanoparticles are innovative agents that could be potentially applicable to in vivo cancer radiotherapy due to the fact that they induce a highly localized energy deposition within the tumor.
      PubDate: 2018-03-26
      DOI: 10.1007/s13246-018-0633-z
  • A simulation study comparing nine mathematical models of arterial input
           function for dynamic contrast enhanced MRI to the Parker model
    • Authors: Dianning He; Lisheng Xu; Wei Qian; James Clarke; Xiaobing Fan
      Abstract: Due to large inter- and intra-patient variabilities of arterial input functions (AIFs), accurately modeling and using patient-specific AIF are very important for quantitative analysis of dynamic contrast enhanced MRI. Computer simulations were performed to evaluate and compare nine population AIF models with the Parker AIF used as ‘gold standard’. The Parker AIF was calculated with a temporal resolution of 1.5 s, and then the other nine AIF models were used to fit the Parker AIF. A total of 100 randomly generated volume transfer constants (Ktrans) and distribution volumes (ve) were used to calculate the contrast agent concentration curves based on the Parker AIF and the extended Tofts model with blood plasma volume (vp) = 0.0, 0.01, 0.05 and 0.10. Subsequently, nine AIF models were used to fit these curves to extract physiological parameters (Ktrans, ve and vp). The agreements between generated and extracted Ktrans and ve values were evaluated using Bland–Altman analysis. The effects of the second pass of the Parker AIF model with and without adding Rician noise on extracted physiological parameters were evaluated by 1000 simulations using one of the nine mathematical AIF models closest to the Parker model with the smallest number of parameters. The results demonstrated that a six-parameter linear function plus bi-exponential function AIF model was almost equivalent to the Parker AIF and that the corresponding generated and extracted Ktrans and ve were in excellent agreements. The effects of the second pass of contrast agent circulation were small on extracted physiological parameters using the extended Tofts model, unless noise was added with signal to noise ratio less than 10 dB.
      PubDate: 2018-03-23
      DOI: 10.1007/s13246-018-0632-0
  • Rejoinder to Letters to the Editor: Luke Wilkinson and Donald McLean, in
           response to Giovanni Bibbo’s letter to the editor: Standardisation of
           shielding of medical X-ray installations
    • Authors: Giovanni Bibbo
      PubDate: 2018-03-22
      DOI: 10.1007/s13246-018-0631-1
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