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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Journal ArticleDOI
Anisotropic Diffusion Filter With Memory Based on Speckle Statistics for Ultrasound Images
Gabriel Ramos-Llordén,Gonzalo Vegas-Sánchez-Ferrero,Marcos Martín-Fernández,Carlos Alberola-López,Santiago Aja-Fernández +4 more
TL;DR: An anisotropic diffusion filter with a probabilistic-driven memory mechanism to overcome the over-filtering problem by following a tissue selective philosophy is proposed and results both in synthetic and real US images support the inclusion of the Probabilistic memory mechanism for maintaining clinical relevant structures, which are removed by the state-of-the-art filters.
Journal ArticleDOI
Despeckling of medical ultrasound images using data and rate adaptive lossy compression
TL;DR: A novel technique for despeckling the medical ultrasound images using lossy compression using the generalized Laplacian distribution and results show that the proposed scheme works better, both in terms of the signal to noise ratio and the visual quality.
Journal ArticleDOI
Echocardiographic speckle reduction comparison
TL;DR: It is concluded that the optimal method is the OSRAD diffusion filter, capable of strong speckle suppression, increasing the average SNRA of the simulated images by a factor of two, and may be efficiently implemented.
Journal ArticleDOI
SRBF: Speckle reducing bilateral filtering.
TL;DR: In this article, a fully automatic bilateral filter tailored to ultrasound images is proposed that is able to tackle the multiplicative behavior modulating the smoothing strength with respect to local statistics, yielding a more homogeneous smoothing.
Journal ArticleDOI
A New Feature-Enhanced Speckle Reduction Method Based on Multiscale Analysis for Ultrasound B-Mode Imaging
TL;DR: It is demonstrated that the proposed FESR method can improve the image quality of ultrasound B-mode imaging by enhancing the visualization of lesion features while effectively suppressing speckle noise.
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