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SUMMARY:Statistical inference in soft-tissue mechanics and fluid dynamics 
 with an application to prognostication of myocardial infarction and pulmon
 ary hypertension - Dirk Husmeier (University of Glasgow)
DTSTART:20190605T143000Z
DTEND:20190605T150000Z
UID:TALK125578@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:A   central problem in biomechanical studies of personalized h
 uman left   ventricular (LV) modelling is estimating the material properti
 es from in-vivo   clinical MRI measurements in a time frame suitable for u
 se in the clinic.   Understanding these properties can provide insight int
 o heart function or   dysfunction and help inform personalised treatment. 
 However\, finding a   solution to the differential equations which describ
 e the myocardium through   numerical integration can be computationally ex
 pensive. To circumvent this   issue\, we use the concept of statistical em
 ulation to infer the myocardium   properties in a viable clinical time fra
 me using in-vivo MRI data. Emulation   methods avoid computationally expen
 sive simulations from the LV model by   replacing it with a surrogate mode
 l inferred from simulations generated   before the arrival of a patient\, 
 vastly improving efficiency at the clinic.   In the talk I will compare an
 d contrast various emulation strategies\, discuss   uncertainty quantifica
 tion and (it time permits) discuss an extension of this   framework to flu
 id dynamics in the pulmonary blood circulation system for   prognosticatio
 n of pulmonary hypertension.
LOCATION:Seminar Room 1\, Newton Institute
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