New neural network algorithm to study myocardial reflected ultrasound for tissue characterization

Cheng Yi, E. Micheli-Tzanakou, Daniel Shindler, John Kostis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Ultrasonic myocardial tissue characterisation is a promising approach to diagnose myocardial infarction since the acoustic properties of myocardial tissue are altered by the disease. We digitize echocardiographic images to study ultrasound backscatter for tissue characterization. Neural network analysis is a successful approach to tissue characterization. We propose to use a new structure of multi-layer perceptron combined with the feedback algorithm ALOPEX.

Original languageEnglish (US)
Title of host publication1993 IEEE 19th Annual Northeasrt Bioengineering Conference
PublisherPubl by IEEE
Pages109-110
Number of pages2
ISBN (Print)0780309251
Publication statusPublished - Jan 1 1993
EventProceedings of the 1993 IEEE 19th Annual Northeast Bioengineering Conference - Newark, NJ, USA
Duration: Mar 18 1993Mar 19 1993

Other

OtherProceedings of the 1993 IEEE 19th Annual Northeast Bioengineering Conference
CityNewark, NJ, USA
Period3/18/933/19/93

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All Science Journal Classification (ASJC) codes

  • Bioengineering

Cite this

Yi, C., Micheli-Tzanakou, E., Shindler, D., & Kostis, J. (1993). New neural network algorithm to study myocardial reflected ultrasound for tissue characterization. In 1993 IEEE 19th Annual Northeasrt Bioengineering Conference (pp. 109-110). Publ by IEEE.