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ULTRASOUND TOMOGRAPHY IMAGING OF DEFECTS USING NEURAL NETWORKS
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UNSPECIFIED (1992) ULTRASOUND TOMOGRAPHY IMAGING OF DEFECTS USING NEURAL NETWORKS. NEURAL COMPUTATION, 4 (5). pp. 758-771.
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Abstract
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 | ||||
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Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry |
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Journal or Publication Title: | NEURAL COMPUTATION | ||||
Publisher: | MIT PRESS | ||||
ISSN: | 0899-7667 | ||||
Official Date: | September 1992 | ||||
Dates: |
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Volume: | 4 | ||||
Number: | 5 | ||||
Number of Pages: | 14 | ||||
Page Range: | pp. 758-771 | ||||
Publication Status: | Published |
Data sourced from Thomson Reuters' Web of Knowledge
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