Japanese Journal of Applied Physics · 2020 · 18 citations · 14 references
EngineeringBiomedical EngineeringBiomedical ImagingComputer VisionUltrasoundAbdominal UltrasonographyDiagnostic UltrasonographyMedical ImagingUltrasonicsUltrasound ImagingUltrasound PhysicsComputer Simulation FrameworksContrastDeep Learning In RadiologyDeep Learning-based Image EnhancementFiltersSignal-to-noise RatioSpeckle Noise ReductionSpeckle Reduction
Abstract Smoothing filters are frequently used for speckle reduction of medical ultrasound images. However, such filters may cause loss of the detailed structures of tissues in terms of image contrast. To improve image contrast in speckle reduction, we investigated a filter for medical ultrasound images using deep learning with a fully convolutional network, which was trained with pairs of input and target data generated by computer simulation. The proposed method achieved higher contrast-to-noise ratio and contrast values than the conventional methods with about 300 times faster processing speed than the NL-means filter.
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A Stochastic Approximation Method
Herbert Robbins, Sutton Monro · The Annals of Mathematical Statistics · 1951 · 9.6K citations · Full text