Multi-Modality Atherosclerosis Imaging and Diagnosis 2013
DOI: 10.1007/978-1-4614-7425-8_13
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A Gamma Mixture Model for IVUS Imaging

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Cited by 9 publications
(7 citation statements)
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“…Distribution 2 drops to 5% of its peak value at an SED duration of 1.9 s, thus validating the use of the biologically-observed 2 s threshold for separating short and long SEDs. The algorithm used for this implementation was obtained from [126].…”
Section: Fig 42 Results Of a Gaussian Mixturementioning
confidence: 99%
See 1 more Smart Citation
“…Distribution 2 drops to 5% of its peak value at an SED duration of 1.9 s, thus validating the use of the biologically-observed 2 s threshold for separating short and long SEDs. The algorithm used for this implementation was obtained from [126].…”
Section: Fig 42 Results Of a Gaussian Mixturementioning
confidence: 99%
“…Using the algorithm and code provided in [126], two components are estimated using the EM algorithm. The mixture density function, g(.…”
Section: State Duration Statisticsmentioning
confidence: 99%
“…They have shown that the Gamma distribution fits both types of data well. Previously, Vegas-Sánchez-Ferrero et al [20], [21] showed that GMM models the gray level distribution of ultrasound images after beam-forming, postprocessing, and interpolation in an accurate and effective way. Therefore, we decided to use a GMM to describe the speckle distribution of our logcompressed gray level data.…”
Section: A Gamma Mixture Modelmentioning
confidence: 99%
“…Therefore, we decided to use a GMM to describe the speckle distribution of our logcompressed gray level data. [9], [10], [21].…”
Section: A Gamma Mixture Modelmentioning
confidence: 99%
“…Then, pcpx, tq is obtained as the a posteriori probability of that class. The parameters of the GMM are estimated by maximizing the log-likelihood function with the Expectation-Maximization algorithm [36], [21], [5].…”
Section: Implementation a The Speckle Characterization Of Pcpx Tqmentioning
confidence: 99%