.css-1xsl8rf{width:100%;display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;position:relative;overflow:hidden;background:var(--alert-bg);-webkit-padding-start:var(--chakra-space-4);padding-inline-start:var(--chakra-space-4);-webkit-padding-end:var(--chakra-space-4);padding-inline-end:var(--chakra-space-4);padding-top:var(--chakra-space-1);padding-bottom:var(--chakra-space-1);--alert-fg:var(--chakra-colors-orange-600);--alert-bg:var(--chakra-colors-orange-100);font-weight:var(--chakra-fontWeights-semibold);padding-left:var(--chakra-space-4);}.chakra-ui-dark .css-1xsl8rf:not([data-theme]),[data-theme=dark] .css-1xsl8rf:not([data-theme]),.css-1xsl8rf[data-theme=dark]{--alert-fg:var(--chakra-colors-orange-200);--alert-bg:rgba(251, 211, 141, 0.16);}@media screen and (min-width: 48em){.css-1xsl8rf{padding-left:var(--chakra-space-8);}}Bitte aktivieren Sie Javascript um alle Funktionen nutzen zu können und ihre Nutzererfahrung zu verbessern.

Prof. Dr. Manfred Schmid Schmid

Erlangen, DE

University hospital,erlangen

Weitere Beteiligungen

28.09.2023
P36
Monitoring of homogenous and heterogenous temperature distributions during hyperthermia of solid tumors by using magnetic resonance-based images as basis for complex-valued U-Net deep-learning models
Quality Assurance, Image guidance, Thermometry, Treatment planning