Neural estimation of scatterer density in ultrasound

被引：2
|
作者：
Smolíková, R [1 ]
Wachowiak, MP [1 ]
Tourassi, GD [1 ]
Zurada, JM [1 ]
机构：
[1] Univ Louisville, Comp Sci & Engn Program, Louisville, KY 40292 USA
来源：
PROCEEDING OF THE 2002 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-3 | 2002年
关键词：
D O I：
10.1109/IJCNN.2002.1007773
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Ultrasonic backscatter can provide information on the density of scatterers within biological media, and is therefore an important tool in tissue characterization. In this paper, a novel neural network approach to estimate scatterer density from generalized entropy is proposed. Neural estimation compares favorably with nonlinear least-squares models.
引用
收藏
页码：1696 / 1701
页数：2
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