ULTRASOUND TOMOGRAPHY IMAGING OF DEFECTS USING NEURAL NETWORKS
UNSPECIFIED (1992) ULTRASOUND TOMOGRAPHY IMAGING OF DEFECTS USING NEURAL NETWORKS. NEURAL COMPUTATION, 4 (5). pp. 758-771. ISSN 0899-7667Full text not available from this repository.
Simulations of ultrasound tomography demonstrated that artificial neural networks can solve the inverse problem in ultrasound tomography. A highly simplified model of ultrasound propagation was constructed, taking no account of refraction or diffraction, and using only longitudinal wave time of flight (TOF). TOF data were used as the network inputs, and the target outputs were the expected pixel maps, showing defects (gray scale coded) according to the velocity of the wave in the defect. The effects of varying resolution and defect velocity were explored. It was found that defects could be imaged using time of flight of ultrasonic rays.
|Item Type:||Journal Item|
|Subjects:||Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
|Journal or Publication Title:||NEURAL COMPUTATION|
|Official Date:||September 1992|
|Number of Pages:||14|
|Page Range:||pp. 758-771|
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