Journal ArticleDOI
Speckle reducing anisotropic diffusion
Yongjian Yu,Scott T. Acton +1 more
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TLDR
This paper provides the derivation of speckle reducing anisotropic diffusion (SRAD), a diffusion method tailored to ultrasonic and radar imaging applications, and validates the new algorithm using both synthetic and real linear scan ultrasonic imagery of the carotid artery.Abstract:
This paper provides the derivation of speckle reducing anisotropic diffusion (SRAD), a diffusion method tailored to ultrasonic and radar imaging applications. SRAD is the edge-sensitive diffusion for speckled images, in the same way that conventional anisotropic diffusion is the edge-sensitive diffusion for images corrupted with additive noise. We first show that the Lee and Frost filters can be cast as partial differential equations, and then we derive SRAD by allowing edge-sensitive anisotropic diffusion within this context. Just as the Lee (1980, 1981, 1986) and Frost (1982) filters utilize the coefficient of variation in adaptive filtering, SRAD exploits the instantaneous coefficient of variation, which is shown to be a function of the local gradient magnitude and Laplacian operators. We validate the new algorithm using both synthetic and real linear scan ultrasonic imagery of the carotid artery. We also demonstrate the algorithm performance with real SAR data. The performance measures obtained by means of computer simulation of carotid artery images are compared with three existing speckle reduction schemes. In the presence of speckle noise, speckle reducing anisotropic diffusion excels over the traditional speckle removal filters and over the conventional anisotropic diffusion method in terms of mean preservation, variance reduction, and edge localization.read more
Citations
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Journal ArticleDOI
Fast feature-preserving speckle reduction for ultrasound images via phase congruency
TL;DR: Experiments demonstrate the proposed novel optimization framework for speckle reduction by leveraging the concept of phase congruency and incorporating a feature asymmetry metric into the regularization term of the objective function to effectively distinguish the features and Speckle noise can better maintain features with speckles removal than state-of-the-art methods.
Computer-aided detection of breast cancer using ultrasound images
Heng-Da Cheng,Yanhui Guo +1 more
TL;DR: A novel enhancement algorithm based on fuzzy logic to enhance the fine details of ultrasound image features, while avoiding noise amplification and over-enhancement, is presented, which takes into account both the fuzzy nature of an ultrasound and feature regions on images, which are significant in diagnosis.
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Object density-based image segmentation and its applications in biomedical image analysis
Jinhua Yu,Jinglu Tan +1 more
TL;DR: An object density-based image segmentation methodology is developed, which incorporates intensity-based, edge-based and texture-based segmentation techniques and is 98% accurate in segmenting synthetic images.
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The Battle of the Video Codecs in the Healthcare Domain - A Comparative Performance Evaluation Study Leveraging VVC and AV1
Andreas S. Panayides,Marios S. Pattichis,Marios Pantziaris,Anthony G. Constantinides,Constantinos S. Pattichis +4 more
TL;DR: This is the first performance comparison of emerging VVC and AV1 video codecs for use in the healthcare domain and demonstrates that VVC outperforms all rival codecs while AV1 achieves better compression efficiency than HEVC in all cases but low-resolution ultrasound videos of the common carotid artery.
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Automated segmentation of transcranial sonographic images in the diagnostics of Parkinson’s disease
Andrius Sakalauskas,Arūnas Lukoševičius,Kristina Laučkaitė,Darius Jegelevičius,Saulius Rutkauskas +4 more
TL;DR: A new technique for automated segmentation applicable to low resolution sonographic images, and particularly to brain structures related to PD, is presented and shown that an automated method is effective when segmentation of the midbrain is performed.
References
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A Computational Approach to Edge Detection
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Journal ArticleDOI
Scale-space and edge detection using anisotropic diffusion
Pietro Perona,Jitendra Malik +1 more
TL;DR: A new definition of scale-space is suggested, and a class of algorithms used to realize a diffusion process is introduced, chosen to vary spatially in such a way as to encourage intra Region smoothing rather than interregion smoothing.
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Digital Image Enhancement and Noise Filtering by Use of Local Statistics
TL;DR: Experimental results show that in most cases the techniques developed in this paper are readily adaptable to real-time image processing.
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A Model for Radar Images and Its Application to Adaptive Digital Filtering of Multiplicative Noise
TL;DR: A model for the radar imaging process is derived and a method for smoothing noisy radar images is presented and it is shown that the filter can be easily implemented in the spatial domain and is computationally efficient.
Journal ArticleDOI
Adaptive speckle filters and scene heterogeneity
A. Lopes,Ridha Touzi,E. Nezry +2 more
TL;DR: The most well known adaptive filters for speckle reduction are analyzed and it is shown that they are based on a test related to the local coefficient of variation of the observed image, which describes the scene heterogeneity.