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Ultrasonographic texture analysis of parenchymatous organs by the four‐neighborhood‐pixels algorithm: clinical experiment.
Author(s) -
Yao W,
Zhao B,
Zhao Y,
Wang W,
Qian G
Publication year - 2001
Publication title -
journal of ultrasound in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.574
H-Index - 91
eISSN - 1550-9613
pISSN - 0278-4297
DOI - 10.7863/jum.2001.20.5.465
Subject(s) - pixel , histogram , texture (cosmology) , algorithm , contrast (vision) , pattern recognition (psychology) , artificial intelligence , image texture , medicine , computer vision , image (mathematics) , computer science , image processing
The parenchyma of organs such as liver, thyroid, and mammary gland during climacterium have common ultrasonographic textural features, which together form what we call small‐dot‐structure texture. To study this texture we designed the 4‐neighborhood‐pixels algorithm, an ultrasonographic texture analysis algorithm. The objective of this study was to confirm whether the 4‐neighborhood‐pixels algorithm can reflect the features of small‐dot‐structure texture. A changed small‐dot‐structure texture and 3 other textures were compared with the normal small‐dot‐structure texture in 4 groups, and a histogram algorithm was used for contrast with the 4‐neighborhood‐pixels algorithm. The 4‐neighborhood‐pixels algorithm could reflect all the textural differences, but the histogram algorithm could reflect only some of them. The 4‐neighborhood‐pixels algorithm is a good algorithm for analyzing ultrasonographic small‐dot‐structure texture. Not only can it reflect changes in the small‐dot‐structure texture, but it can also differentiate between small‐dot‐structure and non‐small‐dot‐structure textures.