Extended-Field-of-View Ultrasound Imaging

Tirumalai, Arun P.; Lowery, Carol; Sutcliffe, Pat; Gustafson, David E.; VonBehren, Pat

doi:10.1117/3.367205.ch6

Cited by 1 publication

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“…The backscattered envelope from tissue was estimated voxel-by-voxel via Nakagami distribution and subsequently used to generate optimized local parametric images for improved liver tumor detection. The assumption is based on that tumor regions tend to have different backscattered distribution than normal tissue [10], and a localized approach based on a varying-size kernel can assist in better identifying the tumor speckle patterns.…”

Section: Introductionmentioning

confidence: 99%

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Notice of Removal Multiscale Nakagami parametric imaging for improved liver tumor localization

Al-Kadi

2016

2016 IEEE International Conference on Image Processing (ICIP)

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Effective ultrasound tissue characterization is usually hindered by complex tissue structures. The interlacing of speckle patterns complicates the correct estimation of backscatter distribution parameters. Nakagami parametric imaging based on localized shape parameter mapping can model different backscattering conditions. However, performance of the constructed Nakagami image depends on the sensitivity of the estimation method to the backscattered statistics and scale of analysis. Using a fixed focal region of interest in estimating the Nakagami parametric image would increase estimation variance. In this work, localized Nakagami parameters are estimated adaptively by means of maximum likelihood estimation on a multiscale basis. The varying size kernel integrates the goodness-of-fit of the backscattering distribution parameters at multiple scales for more stable parameter estimation. Results show improved quantitative visualization of changes in tissue specular reflections, suggesting a potential approach for improving tumor localization in low contrast ultrasound images.

show abstract

Section: Introductionmentioning

confidence: 99%

“…In this work an alternative approach of employing a multi- The assumption is based on that tumor regions tend to have different backscattered distribution than normal tissue [10], and a localized approach based on a varying-size kernel can assist in better identifying the tumor speckle patterns.…”

Section: Introductionmentioning

confidence: 99%

Notice of Removal Multiscale Nakagami parametric imaging for improved liver tumor localization

Al-Kadi

2016

2016 IEEE International Conference on Image Processing (ICIP)

View full text Add to dashboard Cite

show abstract

Extended-Field-of-View Ultrasound Imaging

Cited by 1 publication

References 0 publications

Notice of Removal Multiscale Nakagami parametric imaging for improved liver tumor localization

Notice of Removal Multiscale Nakagami parametric imaging for improved liver tumor localization

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