Thermal imaging is a non-invasive and marker-free approach for intraoperative measurements of small temperature variations. In this work, we demonstrate the abilities of active dynamic thermal imaging for analysis of tissue perfusion state in case of cerebral ischemia. For this purpose, a NaCl irrigation is applied to the exposed cortex during hemicraniectomy. The cortical temperature changes are measured by a thermal imaging system and the thermal signal is recognized by a novel machine learning framework. Subsequent tissue heating is then approximated by a double exponential function to estimate tissue temperature decay constants. These constants allow us to characterize tissue with respect to its dynamic thermal properties. Using a Gaussian mixture model we show the correlation of these estimated parameters with infarct demarcations of post-operative CT. This novel scheme yields a standardized representation of cortical thermodynamic properties and might guide further research regarding specific intraoperative diagnostics.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:30658 |
| Date | 06 June 2018 |
| Creators | Hoffmann, Nico, Drache, Georg, Koch, Edmund, Steiner, Gerald, Kirsch, Matthias, Petersohn, Uwe |
| Publisher | Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | doc-type:workingPaper, info:eu-repo/semantics/workingPaper, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | urn:nbn:de:bsz:14-qucosa-79344, qucosa:24841 |
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