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F20Sonographic tissue characterization based on the parameters derived from computerized processing of gray level data
Author(s) -
Leibovitz Z.,
Degani S.,
Shapiro I.,
Ohel G.
Publication year - 2000
Publication title -
ultrasound in obstetrics and gynecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.202
H-Index - 141
eISSN - 1469-0705
pISSN - 0960-7692
DOI - 10.1046/j.1469-0705.2000.00015-1-20.x
Subject(s) - ultrasound , artificial intelligence , gray level , pixel , medicine , computer vision , image processing , texture (cosmology) , image texture , brightness , region of interest , pattern recognition (psychology) , biomedical engineering , computer science , radiology , image (mathematics) , physics , optics
Background Sonographic tissue characterization is a relatively weak arm of ultrasound diagnosis. There is a great influence of the sonographic machine setup on the B‐mode gray level appearance of the ultrasound image. Various ultrasound artefacts can produce significant changes in brightness setting of the details in sonographic pictures. Nevertheless, in certain situations, the ability to specify the sonographic texture of the tissues may reveal interesting information. Method We present measurable parameters for the specification of the ‘homogenicity’ of the sonographic texture of the scanned tissue. These parameters are derived from the computerized image processing. The processing includes selection of the region of interest, which is related to the specific tissue in the image plane and distribution analysis of the gray level of pixels within the selected region. Results An implication of this algorithm is demonstrated by texture analysis of the different fetal choroid plexus images as they appear in early anatomical scans (15–17 weeks). Of the effects of B‐mode presets – the dynamic range and rejection level had most significant impact on the texture appearance in view of the studied parameters. There was good correlation between the subjective perception of the tissue homogenicity and the computer analysis results. Conclusion The proposed texture parameters may lead to the new approach for the sonographic tissue characterization. These parameters may be used for the standardization of ultrasound machine setups as well.