Proceedings ArticleDOI
Maximum Likelihood signal adaptive filtering of speckle in Ultrasound B-mode images
Michael G. Strintzis,X. Magnisalis,Constantine Kotropoulos,Ioannis Pitas,Nicos Maglaveras +4 more
- Vol. 5, pp 1870-1871
TLDR
A signal-adaptive Maximum Likelihood estimation algorithm is proposed, with local image adaptation based on a moving window, for the processing of Ultrasound (US) B-mode images.Abstract:
New techniques are presented for the processing of Ultrasound (US) B-mode images. A signal-adaptive Maximum Likelihood estimation algorithm is proposed, with local image adaptation based on a moving window. The algorithms are tested on US B-mode images obtained from simulated (phantom) and real liver scans1.read more
Citations
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Journal ArticleDOI
Tracking the left ventricle in echocardiographic images by learning heart dynamics
TL;DR: A temporal learning-filtering procedure is applied to refine the left ventricle (LV) boundary detected by an active-contour model, and this information is incrementally gathered directly from the images and is exploited to achieve more coherent segmentation.
Journal ArticleDOI
Finding the mitral annular lines from 2-D + 1-D precordial echocardiogram using graph-search technique
TL;DR: A nearly automatic method for identifying the mitral annular lines from two-dimensional (2-D) + one-dimensional [1-D] precordial four-chamber view echocardiogram is presented and requires only a physician to provide a point that is always in the left ventricular chamber.
Proceedings ArticleDOI
Wavelet-based enhancement of lesion detectability in ultrasound B-scan images
Alain Rakotomamonjy,P. Marche +1 more
TL;DR: A new technique for enhancing lesion detectability in ultrasound B-scan images is presented, and the present algorithm is superior in lesion detection, and an improvement in the area under ROC curve of the order of 0.1 is observed.
Proceedings ArticleDOI
Left Ventricle Volume Measuring using Echocardiography Sequences
TL;DR: This work proposes adaptive sparse smoothing for left ventricle segmentation for each frame in echocardiography video for the benefit of robustness against strong speckle noise in ultrasound imagery.
Proceedings ArticleDOI
Almost automatic method for reconstruction 3D geometric model of the left ventricle from 3D + 1D precordial echocardiogram
TL;DR: This work designs a method for reconstructing the left ventricles with very few user assists, which should not need too many user assists since there are many images involved.
References
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Probability, random variables and stochastic processes
TL;DR: This chapter discusses the concept of a Random Variable, the meaning of Probability, and the axioms of probability in terms of Markov Chains and Queueing Theory.
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Probability, random variables, and stochastic processes
TL;DR: In this paper, the meaning of probability and random variables are discussed, as well as the axioms of probability, and the concept of a random variable and repeated trials are discussed.
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Nonlinear Digital Filters
TL;DR: This chapter discusses digital filters based on order statistics, Morphological image and signal processing, and Adaptive nonlinear filters.
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Nonlinear Digital Filters : Principles and Applications
TL;DR: In this paper, the authors present a survey of algorithms and architectures for image and signal processing based on order statistics and homomorphies, including adaptive nonlinear filters and median filters.
Journal ArticleDOI
An adaptive weighted median filter for speckle suppression in medical ultrasonic images
TL;DR: In this article, the adaptive weighted median filter (AWMF) is proposed for reducing speckle noise in medical ultrasonic images. But it is not suitable for image segmentation.
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