Literatura académica sobre el tema "Power Doppler parameters"
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Artículos de revistas sobre el tema "Power Doppler parameters"
Sultan, Yasmin. "The Reproducibility of 3D power Doppler in Intrauterine Growth Restriction". Obstetrics Gynecology and Reproductive Sciences 6, n.º 5 (26 de octubre de 2022): 01–07. http://dx.doi.org/10.31579/2578-8965/129.
Texto completoAlgin, Oktay. "Spectral power doppler ultrasound parameters: Are they really significant?" Laryngoscope 119, n.º 7 (14 de mayo de 2009): 1452. http://dx.doi.org/10.1002/lary.20297.
Texto completoDogandzic, A. y B. Zhang. "Estimating Jakes' Doppler power spectrum parameters using the whittle approximation". IEEE Transactions on Signal Processing 53, n.º 3 (marzo de 2005): 987–1005. http://dx.doi.org/10.1109/tsp.2004.842197.
Texto completoLi, Yanhui, Hua Zhao, Ruochen Huang, Geng Zhang, Hangtian Zhou, Chenglin Han y Lu Bai. "Laser Backscattering Analytical Model of Doppler Power Spectra about Convex Quadric Bodies of Revolution during Precession". Remote Sensing 16, n.º 6 (21 de marzo de 2024): 1104. http://dx.doi.org/10.3390/rs16061104.
Texto completoO’Connor, Ewan J., Robin J. Hogan y Anthony J. Illingworth. "Retrieving Stratocumulus Drizzle Parameters Using Doppler Radar and Lidar". Journal of Applied Meteorology 44, n.º 1 (1 de enero de 2005): 14–27. http://dx.doi.org/10.1175/jam-2181.1.
Texto completoKim, Yeong M. y Song B. Park. "Modeling of Doppler Signal considering Sample Volume and Field Distribution". Ultrasonic Imaging 11, n.º 3 (julio de 1989): 175–96. http://dx.doi.org/10.1177/016173468901100302.
Texto completoTamsel, S., G. Demirpolat, M. Erdogan, D. Nart, M. Karadeniz, H. Uluer y A. G. Ozgen. "Power Doppler US patterns of vascularity and spectral Doppler US parameters in predicting malignancy in thyroid nodules". Clinical Radiology 62, n.º 3 (marzo de 2007): 245–51. http://dx.doi.org/10.1016/j.crad.2006.10.003.
Texto completoBabb, David M., Johannes Verlinde y Bruce A. Albrecht. "Retrieval of Cloud Microphysical Parameters from 94-GHz Radar Doppler Power Spectra". Journal of Atmospheric and Oceanic Technology 16, n.º 5 (mayo de 1999): 489–503. http://dx.doi.org/10.1175/1520-0426(1999)016<0489:rocmpf>2.0.co;2.
Texto completoBisi, Melissa Cláudia, Aline Defaveri do Prado, Deise Marcela Piovesan, Markus Bredemeier, Inês Guimarães da Silveira, José Alexandre de Mendonça y Henrique Luiz Staub. "Ultrasound resistive index, power Doppler, and clinical parameters in established rheumatoid arthritis". Clinical Rheumatology 36, n.º 4 (19 de diciembre de 2016): 947–51. http://dx.doi.org/10.1007/s10067-016-3507-3.
Texto completoTozaki, M., M. Toi, Y. Miyamoto y K. Fukuda. "Power Doppler sonography of breast masses: correlation of Doppler spectral parameters with tumor angiogenesis and histologic growth pattern." Journal of Ultrasound in Medicine 19, n.º 9 (septiembre de 2000): 593–600. http://dx.doi.org/10.7863/jum.2000.19.9.593.
Texto completoTesis sobre el tema "Power Doppler parameters"
Abbas, Zeinab. "Predicting the outcome of intracytoplasmic sperm injection in women using machine learning combining Doppler and clinical data : SPIRL". Electronic Thesis or Diss., Le Mans, 2023. http://www.theses.fr/2023LEMA1029.
Texto completoIn-Vitro Fertilization (IVF) and Intra-Cytoplasmic Sperm Injection (ICSI) are now widely used in the treatment of infertility. Patients' primary concern is the success of an IVF treatment, which is dependent on a variety of influencing factors. It is difficult for practitioners to detect any influencing trend of the characteristics and elements that may lead to a successful IVF pregnancy in the absence of automated technology. The goal was to develop a reliable technique for estimating the likelihood of success for couples seeking to conceive: the SPIRL tool (System for Predicting the success Rate of IVF using machine Learning combining clinical and Doppler data). Several factors that contribute to an accomplished pregnancy have been extensively researched. Based on the experience in Al Hadi Centre, the assumption of this work leads on that Power Doppler parameters related to the endometrium and myometrium play a crucial role in the treatment. The first aimed to explore the impact of Doppler parameters, specifically those related to endometrial and myometrium ultrasonography measures, on the success of IVF. The goal was to develop a reliable technique for estimating the likelihood of success for couples seeking to conceive. To achieve this, we evaluated the predictive capabilities of ten different machine learning models, including Logistic Regression, K-Nearest Neighbor, Multilayer Perceptron, Support Vector Machines, Naive Bayes, Bagging Classifier, Gradient Boosting, Extreme Gradient Boosting, AdaBoost Classifier, and Random Forest. These models were trained using a combination of Doppler and clinical parameters. Initially, among the techniques explored for predicting the outcomes of IVF using machine learning, the Bagging method combined with Extra Tree Importance Feature selection demonstrated superior performance for 94 patients. It achieved a sensitivity of 100%, specificity of 80%, and an accuracy of 89.4%. Subsequently, for 572 patients, the Bagging classifier combined with RF importance exhibited the highest AUC of 78.2%. Importantly, several variables, such as myometrium VFI, volume of the endometrium, myometrium mean grey, myometrium FI, myometrium VI, endometrium mean grey, and endometrium FI, were identified as significant factors in the prediction process. These findings underscore the importance of ultrasound measurement parameters, particularly Doppler parameters, in influencing the outcomes of IVF and ICSI. The developed technique provides valuable insights for estimating the success rates of these assisted reproduction procedures. However, these parameters of endometrium and myometrium are currently measured manually using VOCAL software, which is a time-consuming process as it requires calculations based on six slices of the endometrium. The second objective of the work aimed to automatically segment the endometrium to calculate its surface, thickness and endometrial mean grey. Then, we predict the outcome of ICSI using machine learning techniques with the new value. First, we employed automatic and semi-automatic segmentation techniques, specifically the Chan-Vese and Split-Bregman techniques. Out of the 98 ultrasound images, 60 achieved a Jaccard index greater than or equal to 0.5, indicating high-quality segmentation. This accounted for 61% of our initial database. Finally, the third goal was the fully automated version of SPIRL taking our fully automated segmentation technique, which measures the endometrium surface, endometrium mean grey, and endometrium thickness, combined with other clinical features, then classify and predict the outcome of ICSI. the results are closely aligning with the prediction of ICSI outcome using the same features measured by clinicians through ultrasound machines
Stöckel, Chris. "Piezoelektrische Aluminiumnitrid-Dünnschichten für mikroelektromechanische Systeme". Doctoral thesis, Universitätsbibliothek Chemnitz, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-215293.
Texto completoThe thesis includes the design, the technology and the parameter identification of silicon-based microelectromechanical systems (MEMS) with piezoelectric thin film of aluminum nitride (AlN). A low-energy inertial sensor as technology demonstrator based on AlN as an electromechanical transducer a MEMS manufacturing process is shown. The AlN is deposited via a reactive sputtering on a growth layer. By varying parameters of the reactive sputtering and the growth layer of AlN, the piezoelectric properties can be optimized. The development of an overall technology results to an integration of the thin film AlNs in silicon micromechanics. X-ray diffraction (XRD) allows to qualify the crystal structure of AlN. Further methods are developed that enable a highly accurate and repeatable metrological determination of piezoelectric coefficients measurement structures. The determination of piezoelectric coefficients of the thin film AlN from the measurement structures is resulting from analytical methods and FE models and the laser Doppler vibrometry (LDV). The identification of the longitudinal and transverse piezoelectric charge coefficient of AlN is one main focus of this work. A uniaxial inertial sensor with an integrated piezoelectric thin film of AlN is presented as technology demonstrator. The piezoelectric transducer of the MEMS is generating electric charges intrinsically as reaction of mechanical stress. Thus, no electric power supply for the measurement of an inertial event is necessary. The presented demonstrator has been optimized with respect to its charge and voltage sensitivity. For a theoretical description analytical and FE and SPICE models are used. A characterization of the MEMS device is carried out with regard to the mechanical and electrical properties
Libros sobre el tema "Power Doppler parameters"
Kallmeyer, Andrea, José Luis Zamorano, G. Locorotondo, Madalina Garbi, José Juan Gómez de Diego y Miguel Ángel García Fernández. Non-invasive haemodynamic assessment. Oxford University Press, 2011. http://dx.doi.org/10.1093/med/9780199599639.003.0005.
Texto completoCapítulos de libros sobre el tema "Power Doppler parameters"
Ziogas, Apostolos, Emmanouil Xydias y Elias Tsakos. "Novel Methods in the Diagnosis of PCOS: The Role of 3D Ultrasonographic Modalities". En Polycystic Ovary Syndrome [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.101995.
Texto completoActas de conferencias sobre el tema "Power Doppler parameters"
Abbas, Zeinab, Chadi Fakih, Ali Saad y Mohammad Ayache. "Vaginal Power Doppler Parameters as New Predictors of Intra-Cytoplasmic Sperm Injection Outcome". En 2018 International Arab Conference on Information Technology (ACIT). IEEE, 2018. http://dx.doi.org/10.1109/acit.2018.8672713.
Texto completoCanepa, Edward, Pasquale Di Martino, Davide Lengani, Marina Ubaldi y Pietro Zunino. "Radial Swirlers and Mixing Tube Assembly Aerodynamics and Performance Parameters Evaluation: Part 2—LDV Measurements at the Mixing Tube Outlet". En ASME Turbo Expo 2008: Power for Land, Sea, and Air. ASMEDC, 2008. http://dx.doi.org/10.1115/gt2008-51221.
Texto completoRye, Barry J. "Return power estimation for targets spread in range". En Coherent Laser Radar. Washington, D.C.: Optica Publishing Group, 1995. http://dx.doi.org/10.1364/clr.1995.wa2.
Texto completoBecker, Julian y Christoph Hassa. "Experimental Investigation of Spatial and Temporal Aspects of the Liquid Fuel Placement in a Swirl Cup at Elevated Pressure". En ASME Turbo Expo 2004: Power for Land, Sea, and Air. ASMEDC, 2004. http://dx.doi.org/10.1115/gt2004-53524.
Texto completoHage, Michael, Jan Bru¨bach y Andreas Dreizler. "Velocity and Droplet Diameter Distributions of Reacting N-Heptane Sprays at Varied Boundary Conditions in a Generic Gas Turbine Combustor". En ASME Turbo Expo 2010: Power for Land, Sea, and Air. ASMEDC, 2010. http://dx.doi.org/10.1115/gt2010-23378.
Texto completoBatarseh, Feras Z., Ilia V. Roisman y Cam Tropea. "Spray Generated by an Airblast Atomizer at High-Pressure Conditions". En ASME Turbo Expo 2007: Power for Land, Sea, and Air. ASMEDC, 2007. http://dx.doi.org/10.1115/gt2007-27803.
Texto completoAlejandro, S. B. y D. R. Fitzgerald. "Air Force Geophysics Laboratory’s (AFGL) Mobile CO2 Doppler Lidar". En Optical Remote Sensing. Washington, D.C.: Optica Publishing Group, 1985. http://dx.doi.org/10.1364/ors.1985.wc14.
Texto completoLi, Zhigang. "Development and Verification of PWR Physical and Thermal Coupling Calculation Software". En 2020 International Conference on Nuclear Engineering collocated with the ASME 2020 Power Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/icone2020-16106.
Texto completoTan, Tian, Vengatesan Venugopal y Brian Sellar. "Analysis of Turbulence Parameters for a Tidal Energy Site in a Wave-Current Environment". En ASME 2023 42nd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/omae2023-104347.
Texto completoZhao, Yan, Weiwei Shao, Yan Liu, Xiaodi Tang, Yunhan Xiao y Vincent McDonell. "Numerical and Experimental Study of Geometry Effects on Fuel/Air Mixing and Combustion Characteristics of a DLN Burner". En ASME 2020 Power Conference collocated with the 2020 International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/power2020-16371.
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