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<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/"><rdf:Description rdf:about="https://repozitorij.uni-lj.si/IzpisGradiva.php?id=135402"><dc:title>Modelling Uncertainty of Electrical Properties Tomography</dc:title><dc:creator>BELE,	SIMON	(Avtor)
	</dc:creator><dc:creator>Sadikov,	Aleksander	(Mentor)
	</dc:creator><dc:subject>EPT</dc:subject><dc:subject>electrical conductivity</dc:subject><dc:subject>H-EPT</dc:subject><dc:subject>CR-EPT</dc:subject><dc:subject>localisation of pathologies</dc:subject><dc:subject>modelling error</dc:subject><dc:subject>noise.</dc:subject><dc:description>This work uses estimation of error as a way to estimate per voxel data certainty, through which, to the best of our knowledge, we achieve the first known localisation of pathologies in noisy Helmholtz-based EPT reconstructions of brain tissue conductivity. We estimate data certainty by comparing the same voxels across two different conductivity reconstructions (H-EPT
and CR-EPT) as well through estimating boundary error (as the simplified Helmholtz equation used in our data assumed piece-wise constant conductivity) and its propagation through the computation of the spatial derivative required to evaluate the Helmholtz equation.</dc:description><dc:date>2022</dc:date><dc:date>2022-03-11 08:50:01</dc:date><dc:type>Diplomsko delo/naloga</dc:type><dc:identifier>135402</dc:identifier><dc:language>sl</dc:language></rdf:Description></rdf:RDF>