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A Pilot Study on Scatterer Density Classification of Ultrasound Images Using Deep Neural Networks.

, , , , and . EMBC, page 2059-2062. IEEE, (2020)

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Regularized Estimation of Effective Scatterer Size and Acoustic Concentration Quantitative Ultrasound Parameters Using Dynamic Programming*., , , and . EMBC, page 13-16. IEEE, (2020)L1 And L2 Norm Depth-Regularized Estimation Of The Acoustic Attenuation And Backscatter Coefficients Using Dynamic Programming., , , and . ISBI, page 1749-1752. IEEE, (2019)A Pilot Study on Scatterer Density Classification of Ultrasound Images Using Deep Neural Networks., , , , and . EMBC, page 2059-2062. IEEE, (2020)Contrast Optimization in Clinical Contrast-Enhanced Digital Mammography Images., , , , , , , and . Digital Mammography / IWDM, volume 7361 of Lecture Notes in Computer Science, page 17-23. Springer, (2012)Homodyned K-Distribution: Parameter Estimation and Uncertainty Quantification Using Bayesian Neural Networks., , and . ISBI, page 1-4. IEEE, (2023)Analytical Globally-Regularized Estimation Of Effective Scatterer Diameter And Acoustic Concentration in Quantitative Ultrasound., , , and . ISBI, page 1021-1024. IEEE, (2021)Deep Estimation of Speckle Statistics Parametric Images., , and . EMBC, page 3907-3910. IEEE, (2022)Ultrasound Scatterer Density Classification Using Convolutional Neural Networks by Exploiting Patch Statistics., , , , and . CoRR, (2020)Robust Scatterer Number Density Segmentation of Ultrasound Images., , and . CoRR, (2022)Homodyned K-distribution: parameter estimation and uncertainty quantification using Bayesian neural networks., , and . CoRR, (2022)