<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Gander, Lia</dc:creator>
  <dc:creator>Krause, Rolf</dc:creator>
  <dc:creator>Multerer, Michael</dc:creator>
  <dc:creator>Pezzuto, Simone</dc:creator>
  <dc:date>2021-08-19</dc:date>
  <dc:description xmlns:ns0="xml" ns0:lang="en">In electrocardiography, the “classic” inverse problem is the reconstruction of electric potentials at a surface enclosing the heart  from remote recordings at the body surface and an accurate description of the anatomy. The latter being affected by noise and  obtained with limited resolution due to clinical constraints, a possibly large uncertainty may be perpetuated in the inverse  reconstruction. The purpose of this work is to study the effect of shape uncertainty on the forward and the inverse problem of  electrocardiography. To this aim, the problem is first recast into a boundary integral formulation and then discretised with a  collocation method to achieve high convergence rates and a fast time to solution. The shape uncertainty of the domain is  represented by a random deformation field defined on a reference configuration. We propose a periodic-in-time covariance  kernel for the random field and approximate the Karhunen–Loève expansion using low-rank techniques for fast sampling. The  space–time uncertainty in the expected potential and its variance is evaluated with an anisotropic sparse quadrature approach  and validated by a quasi-Monte Carlo method. We present several numerical experiments on a simplified but physiologically  grounded two-dimensional geometry to illustrate the validity of the approach. The tested parametric dimension ranged from  100 up to 600. For the forward problem, the sparse quadrature is very effective. In the inverse problem, the sparse quadrature  and the quasi-Monte Carlo method perform as expected, except for the total variation regularisation, where convergence is  limited by lack of regularity. We finally investigate an H1/2 regularisation, which naturally stems from the boundary integral  formulation, and compare it to more classical approaches.</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>https://n2t.net/ark:/12658/srd1319356</dc:identifier>
  <dc:identifier>https://susi.usi.ch/global/documents/319356</dc:identifier>
  <dc:identifier>https://susi.usi.ch/documents/319356/files/Pezzuto_ijnmbe_2021.pdf</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>info:eu-repo/semantics/altIdentifier/doi/10.1002/cnm.3522</dc:relation>
  <dc:relation>info:eu-repo/semantics/altIdentifier/ark/12658/srd1319356</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>CC BY</dc:rights>
  <dc:source>International journal for numerical methods in biomedical engineering. - Wiley. - 2021, vol. 37, no. 10, p. 23</dc:source>
  <dc:subject xmlns:ns1="xml" ns1:lang="en">H1/2 regularisation</dc:subject>
  <dc:subject xmlns:ns2="xml" ns2:lang="en">Boundary integral formulation</dc:subject>
  <dc:subject xmlns:ns3="xml" ns3:lang="en">Inverse problem of electrocardiography</dc:subject>
  <dc:subject xmlns:ns4="xml" ns4:lang="en">Quasi-Monte Carlo method</dc:subject>
  <dc:subject xmlns:ns5="xml" ns5:lang="en">Space-time shape uncertainty</dc:subject>
  <dc:subject xmlns:ns6="xml" ns6:lang="en">Sparse quadrature</dc:subject>
  <dc:subject>info:eu-repo/classification/udc/61</dc:subject>
  <dc:title xmlns:ns7="xml" ns7:lang="en">Space–time shape uncertainties in the forward and inverse problem of electrocardiography</dc:title>
  <dc:type>http://purl.org/coar/resource_type/c_6501</dc:type>
</oai_dc:dc>
