Book ChapterDOI
Edge Aware Geometric Filter for Ultrasound Image Enhancement
Deepak Mishra,Santanu Chaudhury,Santanu Chaudhury,Mukul Sarkar,Arvinder S. Soin +4 more
- pp 109-120
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TLDR
The proposed filter requires almost no parameter tuning and provides good quality outputs for synthetic as well as real ultrasound images and is compared with the state-of-the-art speckle reducing filters.Abstract:
Despeckling of ultrasound images is essential for subsequent computational analysis. In this paper, an edge aware geometric filter (GF) is proposed for speckle reduction. The behaviour of conventional GF is approximated using commonly used functions like unit step. These approximations help in identifying the natural relationship between GF and other existing spatially adaptive filters. Subsequently, the modifications in GF framework are proposed to take the advantage of edge characteristics. The proposed filter requires almost no parameter tuning and provides good quality outputs for synthetic as well as real ultrasound images. It is compared with the state-of-the-art speckle reducing filters. Improvements of 10.46% and 42% are noticed in mean square error and figure of merit, respectively.read more
Citations
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Journal ArticleDOI
Ultrasound Image Enhancement Using Structure Oriented Adversarial Network
TL;DR: Experimental evaluations show that the proposed DRNN outperforms the state-of-the-art despeckling approaches in terms of the structural similarity index measure, peak signal to noise ratio, edge preservation index, and speckle region's signal-to- noise ratio.
Proceedings ArticleDOI
Despeckling CNN with Ensembles of Classical Outputs
TL;DR: A convolutional neural network is developed which learns to remove speckle from US images using the outputs of these classical approaches and is able to outperform the state-of-the-art despeckling approaches and produces the outputs even better than the ensembles for certain images.
References
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Proceedings ArticleDOI
A model based approach to improve the performance of the geometric filtering speckle reduction algorithm
TL;DR: In this article, the geometric filtering method for speckle reduction in ultrasound images is adapted to ultrasound imaging, where the effects of transducer geometry, center frequency shifts, and beamforming geometry are modeled and used to resample either the raw or video data before speckble processing.
Journal ArticleDOI
Comparison of Despeckle Filters for Breast Ultrasound Images
Zhang Ju,Chen Wang,Yun Cheng +2 more
TL;DR: To objectively and systematically compare the performance of eleven despeckle filters for the breast ultrasound images, several comparison methods are used, such as the full-reference image quality metrics, the nonreference/blind imagequality metrics, observing the removed noise images, as well as the visual evaluation of experts.
Book ChapterDOI
Probabilistic-driven oriented speckle reducing anisotropic diffusion with application to cardiac ultrasonic images
Gonzalo Vegas-Sánchez-Ferrero,Santiago Aja-Fernández,Marcos Martín-Fernández,Alejandro F. Frangi,Cesar Palencia +4 more
TL;DR: A novel anisotropic diffusion filter is proposed in this work which includes probabilistic models which describe the probability density function of tissues and adapts the diffusion tensor to the image iteratively, following the statistical properties of the image in each iteration.
Journal ArticleDOI
Decimated geometric filter for edge-preserving smoothing of non-white image noise
Luciano Alparone,Andrea Garzelli +1 more
TL;DR: A procedure of recursive decimation is proposed to improve the performance of geometric filtering, in the case of spatially correlated image noise, and edges and fine textures are preserved, and noisy backgrounds carefully smoothed in a smaller number of iterations.
Related Papers (5)
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