Use this url to cite publication: https://hdl.handle.net/20.500.12259/98371
Automatic ischemic stroke segmentation using various techniques
Type of publication
Straipsnis konferencijos medžiagoje Web of Science duomenų bazėje / Article in conference proceedings in Web of Science database (P1a1)
Author(s)
| Author | Affiliation | |
|---|---|---|
Usinskas, Andrius | ||
Title
Automatic ischemic stroke segmentation using various techniques
Is part of
Advances in soft computing : neural networks and soft computing : proceedings of the Sixth International Conference on Neural Network and Soft Computing, Zakopane, Poland, June 11-15, 2002. Heidelberg : Physica-Verlag, 2003
Date Issued
| Date |
|---|
2002 |
Publisher
Heidelberg : Physica-Verlag, 2003
Is Referenced by
Extent
p. 498-503
Abstract (en)
Seven different methods aiming at automatic segmentation of human brain ischemic area in the computerized tomography scans are compared. The novel technique, based on the biologically inspired artificial neural networks architecture, is applied for the brain ischemic stroke recognition. The segmentation techniques were evaluated by the experts radiologists. The best viability showed Histogram, Gray level co-occurrence matrix, Mean and standard deviation methods, and Supervised Artificial Neural Networks techniques.
Type of document
type::text::journal::journal article::research article
Language
Anglų / English (en)
Coverage Spatial
Vokietija / Germany (DE)
ISBN (of the container)
3790800058
WOS
WOS:000182433900076
Other Identifier(s)
VDU02-000059051