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ENGINEERING (1209 journals)                  1 2 3 4 5 6 7 | Last

Showing 1 - 200 of 1205 Journals sorted alphabetically
3 Biotech     Open Access   (Followers: 7)
3D Research     Hybrid Journal   (Followers: 19)
AAPG Bulletin     Hybrid Journal   (Followers: 7)
AASRI Procedia     Open Access   (Followers: 15)
Abstract and Applied Analysis     Open Access   (Followers: 3)
Aceh International Journal of Science and Technology     Open Access   (Followers: 2)
ACS Nano     Full-text available via subscription   (Followers: 252)
Acta Geotechnica     Hybrid Journal   (Followers: 7)
Acta Metallurgica Sinica (English Letters)     Hybrid Journal   (Followers: 5)
Acta Polytechnica : Journal of Advanced Engineering     Open Access   (Followers: 2)
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: 11)
Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi     Open Access  
Adsorption     Hybrid Journal   (Followers: 4)
Advanced Engineering Forum     Full-text available via subscription   (Followers: 6)
Advanced Science     Open Access   (Followers: 5)
Advanced Science Focus     Free   (Followers: 3)
Advanced Science Letters     Full-text available via subscription   (Followers: 9)
Advanced Science, Engineering and Medicine     Partially Free   (Followers: 7)
Advanced Synthesis & Catalysis     Hybrid Journal   (Followers: 17)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Complex Systems     Hybrid Journal   (Followers: 7)
Advances in Engineering Software     Hybrid Journal   (Followers: 26)
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: 11)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 22)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 26)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 9)
Advances in Natural Sciences: Nanoscience and Nanotechnology     Open Access   (Followers: 30)
Advances in Operations Research     Open Access   (Followers: 11)
Advances in OptoElectronics     Open Access   (Followers: 5)
Advances in Physics Theories and Applications     Open Access   (Followers: 12)
Advances in Polymer Science     Hybrid Journal   (Followers: 41)
Advances in Porous Media     Full-text available via subscription   (Followers: 4)
Advances in Remote Sensing     Open Access   (Followers: 40)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Aerobiologia     Hybrid Journal   (Followers: 2)
African Journal of Science, Technology, Innovation and Development     Hybrid Journal   (Followers: 5)
AIChE Journal     Hybrid Journal   (Followers: 32)
Ain Shams Engineering Journal     Open Access   (Followers: 5)
Akademik Platform Mühendislik ve Fen Bilimleri Dergisi     Open Access   (Followers: 1)
Alexandria Engineering Journal     Open Access   (Followers: 1)
AMB Express     Open Access   (Followers: 1)
American Journal of Applied Sciences     Open Access   (Followers: 28)
American Journal of Engineering and Applied Sciences     Open Access   (Followers: 11)
American Journal of Engineering Education     Open Access   (Followers: 9)
American Journal of Environmental Engineering     Open Access   (Followers: 17)
American Journal of Industrial and Business Management     Open Access   (Followers: 23)
Analele Universitatii Ovidius Constanta - Seria Chimie     Open Access  
Annals of Combinatorics     Hybrid Journal   (Followers: 3)
Annals of Pure and Applied Logic     Open Access   (Followers: 2)
Annals of Regional Science     Hybrid Journal   (Followers: 8)
Annals of Science     Hybrid Journal   (Followers: 7)
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: 6)
Applied Catalysis B: Environmental     Hybrid Journal   (Followers: 18)
Applied Clay Science     Hybrid Journal   (Followers: 5)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 12)
Applied Magnetic Resonance     Hybrid Journal   (Followers: 4)
Applied Nanoscience     Open Access   (Followers: 8)
Applied Network Science     Open Access   (Followers: 1)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Physics Research     Open Access   (Followers: 3)
Applied Sciences     Open Access   (Followers: 2)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 5)
Arabian Journal for Science and Engineering     Hybrid Journal   (Followers: 5)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 4)
Archives of Foundry Engineering     Open Access  
Archives of Thermodynamics     Open Access   (Followers: 7)
Arkiv för Matematik     Hybrid Journal   (Followers: 1)
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: 1)
Asian Journal of Applied Sciences     Open Access   (Followers: 2)
Asian Journal of Biotechnology     Open Access   (Followers: 8)
Asian Journal of Control     Hybrid Journal  
Asian Journal of Current Engineering & Maths     Open Access  
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  
Australasian Physical & Engineering Sciences in Medicine     Hybrid Journal   (Followers: 1)
Australian Journal of Multi-Disciplinary Engineering     Full-text available via subscription   (Followers: 2)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 9)
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: 1)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 23)
Beni-Suef University Journal of Basic and Applied Sciences     Open Access   (Followers: 4)
BER : Manufacturing Survey : Full Survey     Full-text available via subscription   (Followers: 2)
BER : Motor Trade Survey     Full-text available via subscription   (Followers: 1)
BER : Retail Sector Survey     Full-text available via subscription   (Followers: 2)
BER : Retail Survey : Full Survey     Full-text available via subscription   (Followers: 2)
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: 4)
Bharatiya Vaigyanik evam Audyogik Anusandhan Patrika (BVAAP)     Open Access   (Followers: 1)
Biofuels Engineering     Open Access   (Followers: 1)
Biointerphases     Open Access   (Followers: 1)
Biomaterials Science     Full-text available via subscription   (Followers: 10)
Biomedical Engineering     Hybrid Journal   (Followers: 15)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 14)
Biomedical Engineering Letters     Hybrid Journal   (Followers: 5)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 18)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 34)
Biomedical Engineering: Applications, Basis and Communications     Hybrid Journal   (Followers: 5)
Biomedical Microdevices     Hybrid Journal   (Followers: 9)
Biomedical Science and Engineering     Open Access   (Followers: 4)
Biomedizinische Technik - Biomedical Engineering     Hybrid Journal  
Biomicrofluidics     Open Access   (Followers: 4)
BioNanoMaterials     Hybrid Journal   (Followers: 2)
Biotechnology Progress     Hybrid Journal   (Followers: 39)
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: 10)
Bulletin of Canadian Petroleum Geology     Full-text available via subscription   (Followers: 14)
Bulletin of Engineering Geology and the Environment     Hybrid Journal   (Followers: 14)
Bulletin of the Crimean Astrophysical Observatory     Hybrid Journal  
Cahiers, Droit, Sciences et Technologies     Open Access  
Calphad     Hybrid Journal  
Canadian Geotechnical Journal     Hybrid Journal   (Followers: 30)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 44)
Case Studies in Engineering Failure Analysis     Open Access   (Followers: 8)
Case Studies in Thermal Engineering     Open Access   (Followers: 4)
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     Free   (Followers: 7)
Catalysis Surveys from Asia     Hybrid Journal   (Followers: 3)
Catalysis Today     Hybrid Journal   (Followers: 7)
CEAS Space Journal     Hybrid Journal   (Followers: 1)
Cellular and Molecular Neurobiology     Hybrid Journal   (Followers: 3)
Central European Journal of Engineering     Hybrid Journal   (Followers: 1)
CFD Letters     Open Access   (Followers: 6)
Chaos : An Interdisciplinary Journal of Nonlinear Science     Hybrid Journal   (Followers: 2)
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)
Ciencias Holguin     Open Access   (Followers: 1)
CienciaUAT     Open Access  
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: 14)
City, Culture and Society     Hybrid Journal   (Followers: 24)
Clay Minerals     Full-text available via subscription   (Followers: 10)
Clean Air Journal     Full-text available via subscription   (Followers: 2)
Coal Science and Technology     Full-text available via subscription   (Followers: 3)
Coastal Engineering     Hybrid Journal   (Followers: 11)
Coastal Engineering Journal     Hybrid Journal   (Followers: 5)
Coatings     Open Access   (Followers: 4)
Cogent Engineering     Open Access   (Followers: 2)
Cognitive Computation     Hybrid Journal   (Followers: 4)
Color Research & Application     Hybrid Journal   (Followers: 1)
COMBINATORICA     Hybrid Journal  
Combustion Theory and Modelling     Hybrid Journal   (Followers: 14)
Combustion, Explosion, and Shock Waves     Hybrid Journal   (Followers: 13)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications in Numerical Methods in Engineering     Hybrid Journal   (Followers: 2)
Components, Packaging and Manufacturing Technology, IEEE Transactions on     Hybrid Journal   (Followers: 27)
Composite Interfaces     Hybrid Journal   (Followers: 6)
Composite Structures     Hybrid Journal   (Followers: 268)
Composites Part A : Applied Science and Manufacturing     Hybrid Journal   (Followers: 194)
Composites Part B : Engineering     Hybrid Journal   (Followers: 272)
Composites Science and Technology     Hybrid Journal   (Followers: 192)
Comptes Rendus Mécanique     Full-text available via subscription   (Followers: 2)
Computation     Open Access  
Computational Geosciences     Hybrid Journal   (Followers: 15)
Computational Optimization and Applications     Hybrid Journal   (Followers: 7)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 8)
Computer Science and Engineering     Open Access   (Followers: 19)
Computers & Geosciences     Hybrid Journal   (Followers: 29)
Computers & Mathematics with Applications     Full-text available via subscription   (Followers: 6)
Computers and Electronics in Agriculture     Hybrid Journal   (Followers: 4)
Computers and Geotechnics     Hybrid Journal   (Followers: 11)
Computing and Visualization in Science     Hybrid Journal   (Followers: 6)
Computing in Science & Engineering     Full-text available via subscription   (Followers: 32)
Conciencia Tecnologica     Open Access  
Concurrent Engineering     Hybrid Journal   (Followers: 3)
Continuum Mechanics and Thermodynamics     Hybrid Journal   (Followers: 7)
Control and Dynamic Systems     Full-text available via subscription   (Followers: 9)
Control Engineering Practice     Hybrid Journal   (Followers: 43)
Control Theory and Informatics     Open Access   (Followers: 8)
Corrosion Science     Hybrid Journal   (Followers: 25)
Corrosion Series     Full-text available via subscription   (Followers: 6)
CT&F Ciencia, Tecnologia y Futuro     Open Access   (Followers: 1)

        1 2 3 4 5 6 7 | Last

Journal Cover Australasian Physical & Engineering Sciences in Medicine
  [SJR: 0.293]   [H-I: 19]   [1 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0158-9938 - ISSN (Online) 1879-5447
   Published by Springer-Verlag Homepage  [2355 journals]
  • “Revise before review; Reject without review; Reject after review”:
           why manuscripts are rejected
    • Authors: Martin Caon
      PubDate: 2018-01-09
      DOI: 10.1007/s13246-018-0615-1
  • GATE Monte Carlo simulation of dose distribution using MapReduce in a
           cloud computing environment
    • Authors: Yangchuan Liu; Yuguo Tang; Xin Gao
      Pages: 777 - 783
      Abstract: Abstract The GATE Monte Carlo simulation platform has good application prospects of treatment planning and quality assurance. However, accurate dose calculation using GATE is time consuming. The purpose of this study is to implement a novel cloud computing method for accurate GATE Monte Carlo simulation of dose distribution using MapReduce. An Amazon Machine Image installed with Hadoop and GATE is created to set up Hadoop clusters on Amazon Elastic Compute Cloud (EC2). Macros, the input files for GATE, are split into a number of self-contained sub-macros. Through Hadoop Streaming, the sub-macros are executed by GATE in Map tasks and the sub-results are aggregated into final outputs in Reduce tasks. As an evaluation, GATE simulations were performed in a cubical water phantom for X-ray photons of 6 and 18 MeV. The parallel simulation on the cloud computing platform is as accurate as the single-threaded simulation on a local server and the simulation correctness is not affected by the failure of some worker nodes. The cloud-based simulation time is approximately inversely proportional to the number of worker nodes. For the simulation of 10 million photons on a cluster with 64 worker nodes, time decreases of 41× and 32× were achieved compared to the single worker node case and the single-threaded case, respectively. The test of Hadoop’s fault tolerance showed that the simulation correctness was not affected by the failure of some worker nodes. The results verify that the proposed method provides a feasible cloud computing solution for GATE.
      PubDate: 2017-12-01
      DOI: 10.1007/s13246-017-0580-0
      Issue No: Vol. 40, No. 4 (2017)
  • Heartbeat detection in multimodal physiological signals using signal
           quality assessment based on sample entropy
    • Authors: Omkar Singh; Ramesh Kumar Sunkaria
      Pages: 917 - 923
      Abstract: Abstract This paper presents a novel technique to identify heartbeats in multimodal data using electrocardiogram (ECG) and arterial blood pressure (ABP) signals. Multiple physiological signals such as ECG, ABP, and Respiration are often recorded in parallel from the activity of heart. These signals generally possess related information as they are generated by the same physical system. The ECG and ABP correspond to the same phenomenon of contraction and relaxation activity of heart. Multiple signals acquired from various sensors are generally processed independently, thus discarding the information from other measurements. In the estimation of heart rate and heart rate variability, the R peaks are generally identified from ECG signal. Efficient detection of R-peaks in electrocardiogram (ECG) is a key component in the estimation of clinically relevant parameters from ECG. However, when the signal is severely affected by undesired artifacts, this becomes a challenging task. Sometimes in clinical environment, other physiological signals reflecting the cardiac activity such as ABP signal are also acquired simultaneously. Under the availability of such multimodal signals, the accuracy of R peak detection methods can be improved using sensor-fusion techniques. In the proposed method, the sample entropy (SampEn) is used as a metric for assessing the noise content in the physiological signal and the R peaks in ECG and the systolic peaks in ABP signals are fused together to enhance the efficiency of heartbeat detection. The proposed method was evaluated on the 100 records from the computing in cardiology challenge 2014 training data set. The performance parameters are: sensitivity (Se) and positive predictivity (PPV). The unimodal R peaks detector achieved: Se gross = 99.40%, PPV gross = 99.29%, Se average = 99.37%, PPV average = 99.29%. Similarly unimodal BP delineator achieved Se gross = 99.93%, PPV gross = 99.99%, Se average = 99.93%, PPV average = 99.99% whereas, the proposed multimodal beat detector achieved: Se gross = 99.65%, PPV gross = 99.91%, Se average = 99.68%, PPV average = 99.91%.
      PubDate: 2017-12-01
      DOI: 10.1007/s13246-017-0585-8
      Issue No: Vol. 40, No. 4 (2017)
  • The effect of beam interruption during FFF-VMAT plans for SBRT
    • Authors: Seongjong Oh; Benjamin Lewis; Amy Watson; Siyong Kim; Taeho Kim
      Pages: 931 - 938
      Abstract: Abstract To investigate the dosimetric effect of intended beam interruption during volumetric modulated arc therapy (VMAT) with flattening filter free (FFF) beam for exploring the possibility of deep inspiration breath hold stereotactic body radiation therapy (SBRT). A total of ten SBRT plans with 6 and 10 MV FFF beams were retrospectively selected. All plans consisted of four partial arcs, except one plan with six partial arcs. We delivered the plans using a Varian Truebeam™ with three different scenarios; without interruption (0int), with one intentional interruption (1int), or with two intentional interruptions (2int), per each partial arc. The treatment log files were exported from the treatment console, and the variations in delivered MU were evaluated at the beam interruption angles. The dose distributions were also measured using a 3D cylindrical diode array detector, ArcCHECK™. The 2D global gamma evaluations were performed, compared to the planned dose distribution, with 3%/3 and 4%/2 mm passing criterion. The dose difference (DD) was also determined between uninterrupted and interrupted data with 3, 2, 1, and 0.5% of global maximum dose. The interruption caused a total increase of 0.14 ± 0.05% and 0.25 ± 0.08% of the total planned MU, ranging from 1746 to 3261 MU, at the interrupted angles in 1int and 2int, respectively. All global gamma passing rates satisfied our clinical threshold of 90%, and the differences of passing rates were less than 0.3% on average with both criterions. All measured 1int and 2int data were within 3% DD from 0int measured data. For 6 MV FFF beams, the average passing rate with 2, 1, and 0.5% DD were 99.9 ± 0.2%, 92.3 ± 12.0%, and 81.9 ± 24.9%, respectively, between 0int and 1int, and 99.8 ± 0.4%, 92.1%12.4%, and 80.7 ± 26.5%, respectively, between 0int and 2int. For 10 MV FFF beams, the average passing rate with 2, 1, and 0.5% DD were 100.0 ± 0.2%, 95.4 ± 9.4% and 87.0 ± 19.8%, respectively, between 0int and 1int, and 99.9 ± 0.3%, 95.4 ± 9.7%, and 87.2 ± 21.3% between 0int and 2int. The dosimetric impact of beam interruption was investigated with small field and high dose rate FFF-VMAT SBRT plans. The delivered dose distributions with up to 12 interruptions per plan were still clinically acceptable. Only minimal changes were observed in Gamma, DD, and log file analysis.
      PubDate: 2017-12-01
      DOI: 10.1007/s13246-017-0588-5
      Issue No: Vol. 40, No. 4 (2017)
  • Author Index Volume 40
    • Pages: 955 - 959
      PubDate: 2017-12-01
      DOI: 10.1007/s13246-017-0608-5
      Issue No: Vol. 40, No. 4 (2017)
  • Application of image recognition-based automatic hyphae detection in
           fungal keratitis
    • Authors: Xuelian Wu; Yuan Tao; Qingchen Qiu; Xinyi Wu
      Abstract: Abstract The purpose of this study is to evaluate the accuracy of two methods in diagnosis of fungal keratitis, whereby one method is automatic hyphae detection based on images recognition and the other method is corneal smear. We evaluate the sensitivity and specificity of the method in diagnosis of fungal keratitis, which is automatic hyphae detection based on image recognition. We analyze the consistency of clinical symptoms and the density of hyphae, and perform quantification using the method of automatic hyphae detection based on image recognition. In our study, 56 cases with fungal keratitis (just single eye) and 23 cases with bacterial keratitis were included. All cases underwent the routine inspection of slit lamp biomicroscopy, corneal smear examination, microorganism culture and the assessment of in vivo confocal microscopy images before starting medical treatment. Then, we recognize the hyphae images of in vivo confocal microscopy by using automatic hyphae detection based on image recognition to evaluate its sensitivity and specificity and compare with the method of corneal smear. The next step is to use the index of density to assess the severity of infection, and then find the correlation with the patients’ clinical symptoms and evaluate consistency between them. The accuracy of this technology was superior to corneal smear examination (p < 0.05). The sensitivity of the technology of automatic hyphae detection of image recognition was 89.29%, and the specificity was 95.65%. The area under the ROC curve was 0.946. The correlation coefficient between the grading of the severity in the fungal keratitis by the automatic hyphae detection based on image recognition and the clinical grading is 0.87. The technology of automatic hyphae detection based on image recognition was with high sensitivity and specificity, able to identify fungal keratitis, which is better than the method of corneal smear examination. This technology has the advantages when compared with the conventional artificial identification of confocal microscope corneal images, of being accurate, stable and does not rely on human expertise. It was the most useful to the medical experts who are not familiar with fungal keratitis. The technology of automatic hyphae detection based on image recognition can quantify the hyphae density and grade this property. Being noninvasive, it can provide an evaluation criterion to fungal keratitis in a timely, accurate, objective and quantitative manner.
      PubDate: 2017-12-28
      DOI: 10.1007/s13246-017-0613-8
  • Epileptic seizure detection in EEG signal using machine learning
    • Authors: Abeg Kumar Jaiswal; Haider Banka
      Abstract: Abstract Epilepsy is a well-known nervous system disorder characterized by seizures. Electroencephalograms (EEGs), which capture brain neural activity, can detect epilepsy. Traditional methods for analyzing an EEG signal for epileptic seizure detection are time-consuming. Recently, several automated seizure detection frameworks using machine learning technique have been proposed to replace these traditional methods. The two basic steps involved in machine learning are feature extraction and classification. Feature extraction reduces the input pattern space by keeping informative features and the classifier assigns the appropriate class label. In this paper, we propose two effective approaches involving subpattern based PCA (SpPCA) and cross-subpattern correlation-based PCA (SubXPCA) with Support Vector Machine (SVM) for automated seizure detection in EEG signals. Feature extraction was performed using SpPCA and SubXPCA. Both techniques explore the subpattern correlation of EEG signals, which helps in decision-making process. SVM is used for classification of seizure and non-seizure EEG signals. The SVM was trained with radial basis kernel. All the experiments have been carried out on the benchmark epilepsy EEG dataset. The entire dataset consists of 500 EEG signals recorded under different scenarios. Seven different experimental cases for classification have been conducted. The classification accuracy was evaluated using tenfold cross validation. The classification results of the proposed approaches have been compared with the results of some of existing techniques proposed in the literature to establish the claim.
      PubDate: 2017-12-20
      DOI: 10.1007/s13246-017-0610-y
  • A principal component analysis based data fusion method for ECG-derived
           respiration from single-lead ECG
    • Authors: Yue Gao; Hong Yan; Zhi Xu; Meng Xiao; Jinzhong Song
      Abstract: Abstract An ECG-derived respiration (EDR) algorithm based on principal component analysis (PCA) is presented and applied to derive the respiratory signals from single-lead ECG. The respiratory-induced variabilities of ECG features, P-peak amplitude, Q-peak amplitude, R-peak amplitude, S-peak amplitude, T-peak amplitude and RR-interval, are fused by PCA to yield a better surrogate respiratory signal than other methods. The method is evaluated on data from the MIT-BIH polysomnographic database and validated against a “gold standard” respiratory obtained from simultaneously recorded respiration data. The performance of fusion algorithm is assessed by comparing the EDR signals to a reference respiratory signal, using the quantitative evaluation indexes that include true positive (TP), false positive (FP), false negative (FN), sensitivity (SE) and positive predictivity (PP). The statistically difference is significant among the PCA data fusion method and the EDR methods based on the RR intervals and the RS amplitudes, showing that PCA data fusion algorithm outperforms the others in the extraction of respiratory signals from single-lead ECGs.
      PubDate: 2017-12-19
      DOI: 10.1007/s13246-017-0612-9
  • Feasibility study for production and quality control of Yb-175 as a
           byproduct of no carrier added Lu-177 preparation for radiolabeling of
    • Authors: Nafise Salek; Simindokht Shirvani Arani; Ali Bahrami Samani; Sara Vosoghi; Mohsen Mehrabi
      Abstract: Abstract Skeletal uptake of β− emitters of DOTMP complexes is used for the bone pain palliation. In this study, two moderate energy β− emitters, 177Lu (T1/2 = 6.7 days, Eβmax = 497 keV) and 175Yb (T1/2 = 4.2 days, Eβmax = 480 keV), are considered as potential agents for the development of the bone-seeking radiopharmaceuticals. Since the specific activity of the radiolabelled carrier molecules should be high, the non-carrier-added (NCA) radionuclides have an effective role in nuclear medicine. Many researchers have presented the synthesis of NCA 177Lu. Among these separation techniques, extraction chromatography has been considered more capable than other methods. In this study, a new approach, in addition to production of NCA 177Lu by EXC procedure is using pure 175Yb that was usually considered as a waste material in this method but because of high radionuclidic purity of 175Yb produced by this method we used it for radiolabeling as well as NCA 177Lu. To obtain optimum conditions, some effective factors on separation of Lu/Yb by EXC were investigated. The NCA 177Lu and pure 175Yb were produced with radionuclidic purity of 99.99 and 99.97% respectively by irradiation of enriched 176Yb target in thermal neutron flux of 5 × 1013 n/cm2 s for 14 days. 177Lu-DOTMP and 175Yb-DOTMP were obtained with high radiochemical purities (> 95%) under optimized reaction conditions. Two radiolabeled complexes exhibited excellent stability at room temperature. Biodistribution studies in rats showed favorable selective skeletal uptake with rapid clearance from blood along with insignificant accumulation of activity in other non-target organs for two radiolabelled complexes.
      PubDate: 2017-12-19
      DOI: 10.1007/s13246-017-0611-x
  • A novel fully automatic multilevel thresholding technique based on
           optimized intuitionistic fuzzy sets and tsallis entropy for MR brain tumor
           image segmentation
    • Authors: Taranjit Kaur; Barjinder Singh Saini; Savita Gupta
      Abstract: Abstract In the present paper, a hybrid multilevel thresholding technique that combines intuitionistic fuzzy sets and tsallis entropy has been proposed for the automatic delineation of the tumor from magnetic resonance images having vague boundaries and poor contrast. This novel technique takes into account both the image histogram and the uncertainty information for the computation of multiple thresholds. The benefit of the methodology is that it provides fast and improved segmentation for the complex tumorous images with imprecise gray levels. To further boost the computational speed, the mutation based particle swarm optimization is used that selects the most optimal threshold combination. The accuracy of the proposed segmentation approach has been validated on simulated, real low-grade glioma tumor volumes taken from MICCAI brain tumor segmentation (BRATS) challenge 2012 dataset and the clinical tumor images, so as to corroborate its generality and novelty. The designed technique achieves an average Dice overlap equal to 0.82010, 0.78610 and 0.94170 for three datasets. Further, a comparative analysis has also been made between the eight existing multilevel thresholding implementations so as to show the superiority of the designed technique. In comparison, the results indicate a mean improvement in Dice by an amount equal to 4.00% (p < 0.005), 9.60% (p < 0.005) and 3.58% (p < 0.005), respectively in contrast to the fuzzy tsallis approach.
      PubDate: 2017-12-13
      DOI: 10.1007/s13246-017-0609-4
  • Development of GATE Monte Carlo simulation for a CsI pixelated gamma
           camera dedicated to high resolution animal SPECT
    • Authors: Payvand Taherparvar; Alireza Sadremomtaz
      Abstract: Abstract GATE is currently considered in scintigraphic imaging as a powerful tool to develop, design and optimize nuclear medicine modalities. This paper describes the GATE simulation of a pixelated gamma camera which is dedicated to high resolution of small animals imaging. It consists of a CsI(Na) crystal array coupled to position sensitive photomultiplier tube. The simulation model includes photon tracking through low energy high resolution hexagonal parallel holes collimator, CsI(Na) pixelated crystal, back-compartment, and camera shielding. Simulations were compared with experimental results by some criteria such as energy spectrum, energy resolution, spatial resolution, sensitivity and count profiles obtained from line and point sources imaging. The acquired energy resolution show good agreement with measured spectra. Difference between calculated and experimental values is about 0.3% for absolute sensitivity measurement. The result of the image uniformity is more consistent after implementation of non-uniformity correction. These values were about 1.3 and 1.2% for experimental and simulation study in the central field of view, respectively. Measurements showed that the spatial resolutions differences at the head surface along the long dimensions of gamma camera for simulation and experimental differed by no more than 4%.Differences along the short axis were about 6%. The FWHMs of images of point and line sources show good consistency between experimental images and corresponding simulated ones. The difference between experimental and simulated system parameters was within 11%. Our results demonstrate the ability and flexibility of the Monte Carlo simulation for modeling pixelated gamma camera with position sensitive detector by selecting the appropriate parameters for digitizer chain and collimator position on the detector surface.
      PubDate: 2017-12-11
      DOI: 10.1007/s13246-017-0607-6
  • Effects of visual and cognitive interference on joint contributions in
           perturbed standing: a temporal and spectral analysis
    • Authors: Mohammed N. Ashtiani; Mahmood-reza Azghani
      Abstract: Abstract Postural balance requires using joint strategies which may be changed from normal conditions by interfering with the sensory information. The goal of the present study was to quantitatively evaluate the role of the joint mechanisms during perturbed stance. Visual and cognitive interference was imposed to sixteen healthy young males under rotational toes-down or up perturbations. Power spectral analysis was employed to distinguish the joint contribution and their in- or out-phase co-works. Results showed that addition of cognitive loads reduce the stability by increasing the center of mass (CoM) power to three times greater. Besides the CoM, the knee and hip powers were also significantly enhanced by the cognitive loads (p < .004), but the ankle was not influenced by cognition involvement (p > .05). Elimination of the vision had lower effect on the time and spectral functions of the knee and hip while the ankle rotations were increased due to the lack of visual feedback (p = .001). The toes-down perturbations resulted in more prominent contribution of the knee while the toes-up evoked the hip joint to keep the balance more than the other joints. Addition of the cognitive loads hindered the reactions of the joint mechanisms and vision caused more conservative responses of the joints.
      PubDate: 2017-12-05
      DOI: 10.1007/s13246-017-0606-7
  • Risks posed by neutron contamination in high energy radiotherapy
    • PubDate: 2017-11-30
      DOI: 10.1007/s13246-017-0603-x
  • Medical physics publishing in a changing research environment: the
           Australasian Physical & Engineering Sciences in Medicine 40th
           anniversary editorial
    • Authors: Scott B. Crowe; Tanya Kairn
      PubDate: 2017-11-29
      DOI: 10.1007/s13246-017-0602-y
  • Acknowledgement of APESM reviewers for Volume 40
    • PubDate: 2017-11-29
      DOI: 10.1007/s13246-017-0600-0
  • Assessment of the relative contribution of volume and concentration
           changes in Yttrium-90 labelled resin microspheres on ionization chamber
    • Authors: Nicholas Forwood; Kathy P. Willowson; Michael Tapner; Dale L. Bailey
      PubDate: 2017-11-17
      DOI: 10.1007/s13246-017-0601-z
  • Accuracy of the Garmin 920 XT HRM to perform HRV analysis
    • Authors: Johan Cassirame; Romain Vanhaesebrouck; Simon Chevrolat; Laurent Mourot
      Abstract: Abstract Heart rate variability (HRV) analysis is widely used to investigate autonomous cardiac drive. This method requires periodogram measurement, which can be obtained by an electrocardiogram (ECG) or from a heart rate monitor (HRM), e.g. the Garmin 920 XT device. The purpose of this investigation was to assess the accuracy of RR time series measurements from a Garmin 920 XT HRM as compared to a standard ECG, and to verify whether the measurements thus obtained are suitable for HRV analysis. RR time series were collected simultaneously with an ECG (Powerlab system, AD Instruments, Castell Hill, Australia) and a Garmin XT 920 in 11 healthy subjects during three conditions, namely in the supine position, the standing position and during moderate exercise. In a first step, we compared RR time series obtained with both tools using the Bland and Altman method to obtain the limits of agreement in all three conditions. In a second step, we compared the results of HRV analysis between the ECG RR time series and Garmin 920 XT series. Results show that the accuracy of this system is in accordance with the literature in terms of the limits of agreement. In the supine position, bias was 0.01, − 2.24, + 2.26 ms; in the standing position, − 0.01, − 3.12, + 3.11 ms respectively, and during exercise, − 0.01, − 4.43 and + 4.40 ms. Regarding HRV analysis, we did not find any difference for HRV analysis in the supine position, but the standing and exercise conditions both showed small modifications.
      PubDate: 2017-10-20
      DOI: 10.1007/s13246-017-0593-8
  • Successful implementation of Virtual Environment for Radiotherapy Training
           (VERT) in Medical Physics education: The University of Sydney’s initial
           experience and recommendations
    • Authors: Yobelli A. Jimenez; Christian Rønn Hansen; Prabhjot Juneja; David I. Thwaites
      Abstract: Abstract This report outlines the University of Sydney’s initial experience with the Virtual Environment for Radiotherapy Training (VERT) system in the Master of Medical Physics program. VERT is a commercially available system, simulating linear accelerators, patient computed tomography (CT) sets, plans and treatment delivery. It was purpose built for radiation therapy (RT) education and offers learners the opportunity to gain knowledge and skills within an interactive, risk-free environment. The integration of VERT into the RT physics module of the Master of Medical Physics program was intended to enhance student knowledge and skills relevant to the curriculum’s learning objectives, and to alleviate some of the burden associated with student access to clinical equipment. Three VERT practical sessions were implemented: “RT treatment planning systems”, “(CT) Anatomy for physicists” and “Linear accelerator measurements”. Our experience and student evaluations were positive and demonstrated the viability of VERT for medical physics (MP) student education. We anticipate that integration of VERT into MP teaching is a valuable addition to traditional methods and can aid MP students’ understanding and readiness for practice. Additional evaluations should be conducted to ascertain VERT’s role in delivering efficient quantity and quality of MP education, and its potential in alleviating burdens placed on clinical departments.
      PubDate: 2017-10-13
      DOI: 10.1007/s13246-017-0592-9
  • Proposed patient motion monitoring system using feature point tracking
           with a web camera
    • Authors: Hideharu Miura; Shuichi Ozawa; Takaaki Matsuura; Kiyoshi Yamada; Yasushi Nagata
      Abstract: Abstract Patient motion monitoring systems play an important role in providing accurate treatment dose delivery. We propose a system that utilizes a web camera (frame rate up to 30 fps, maximum resolution of 640 × 480 pixels) and an in-house image processing software (developed using Microsoft Visual C++ and OpenCV). This system is simple to use and convenient to set up. The pyramidal Lucas–Kanade method was applied to calculate motions for each feature point by analysing two consecutive frames. The image processing software employs a color scheme where the defined feature points are blue under stable (no movement) conditions and turn red along with a warning message and an audio signal (beeping alarm) for large patient movements. The initial position of the marker was used by the program to determine the marker positions in all the frames. The software generates a text file that contains the calculated motion for each frame and saves it as a compressed audio video interleave (AVI) file. We proposed a patient motion monitoring system using a web camera, which is simple and convenient to set up, to increase the safety of treatment delivery.
      PubDate: 2017-10-06
      DOI: 10.1007/s13246-017-0589-4
  • Shielding of medical imaging X-ray facilities: a simple and practical
    • Authors: Giovanni Bibbo
      Abstract: Abstract The most widely accepted method for shielding design of X-ray facilities is that contained in the National Council on Radiation Protection and Measurements Report 147 whereby the computation of the barrier thickness for primary, secondary and leakage radiations is based on the knowledge of the distances from the radiation sources, the assumptions of the clinical workload, and usage and occupancy of adjacent areas. The shielding methodology used in this report is complex. With this methodology, the shielding designers need to make assumptions regarding the use of the X-ray room and the adjoining areas. Different shielding designers may make different assumptions resulting in different shielding requirements for a particular X-ray room. A more simple and practical method is to base the shielding design on the shielding principle used to shield X-ray tube housing to limit the leakage radiation from the X-ray tube. In this case, the shielding requirements of the X-ray room would depend only on the maximum radiation output of the X-ray equipment regardless of workload, usage or occupancy of the adjacent areas of the room. This shielding methodology, which has been used in South Australia since 1985, has proven to be practical and, to my knowledge, has not led to excess shielding of X-ray installations.
      PubDate: 2017-10-05
      DOI: 10.1007/s13246-017-0586-7
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