DocumentCode
3092434
Title
Higher-order statistics for tissue characterization from ultrasound images
Author
Abeyratne, Udantha R. ; Petropulu, Athina P.
Author_Institution
Dept. of Electr. & Comput. Eng., Drexel Univ., Philadelphia, PA, USA
fYear
1997
fDate
21-23 Jul 1997
Firstpage
72
Lastpage
76
Abstract
We model tissue as a collection of point scatterers embedded in a uniform media, and show that the higher order statistics (HOS) of the scatterer spacing distribution can be estimated from digitized RF scan line segments and be used in obtaining tissue signatures. Based on our model for tissue microstructure, we estimate resolvable periodicity and correlations among non-periodic scatterers. Using higher-order statistics of the scattered signal, we define as tissue “color” a quantity that describes the scatterer spatial correlations, show how to estimate it from the higher-order correlations of the digitized RF scan line segments, and investigate its potential as a tissue signature
Keywords
biomedical ultrasonics; correlation methods; higher order statistics; image segmentation; liver; clinical images; correlations; digitized RF scan line segments; higher-order correlations; higher-order statistics; human livers; model; nonperiodic scatterers; point scatterers; resolvable periodicity estimation; scatterer spacing distribution; scatterer spatial correlations; tissue characterization; tissue microstructure; tissue signature; tissue signatures; tumors; ultrasound images; Acoustic scattering; Biological tissues; Embedded computing; Higher order statistics; Image segmentation; Liver diseases; Microstructure; RF signals; Radio frequency; Ultrasonic imaging;
fLanguage
English
Publisher
ieee
Conference_Titel
Higher-Order Statistics, 1997., Proceedings of the IEEE Signal Processing Workshop on
Conference_Location
Banff, Alta.
Print_ISBN
0-8186-8005-9
Type
conf
DOI
10.1109/HOST.1997.613490
Filename
613490
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