Ultrasound image Uniformity Assessment by Means of Sparse Matrices: Algorithm Implementation and First Results

• Abstract:

  The current study is focused on an image segmentation algorithm for Uniformity Quality assessment in Diagnostic Ultrasounds.In particular a mathematical definition of the uniformity in ultrasound images is introducedand a split and merge algorithm performed on sparse matricesto measure uniformity is described. The algorithm is based on the Gray-Level Co-occurrence Matrices and the relativedescriptors,i.e. the Haralick features Entropy, Energy, Maximal CorrelationCoefficientand InformationMeasures of Correlation.Results on2 differentdatasetsof test images with different nonuniformities have been carried on. Several outcomesshow a goodsensitivity and agreement with the mean judgment by 7 human observers, i.e. differences are below 40% in most of the cases.On the basis of previousstudies, the latest developments and results are proposed and commented.
• Keywords:

  Uniformity measurement, ultrasound, speckle, Gray Level Co-occurrence Matrix, Haralick features
• Download:

  IMEKO-TC4-2017-031.pdf
• DOI:

  _unreg_tc4-2017.031

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