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Computation-Enhanced Surgery and Intervention: An Engineering Exemplar in Translation

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While modern medical imaging coupled to contemporary image processing and informatics has allowed for
dramatic expansions of diagnostic information, similar advances in procedural medicine have lagged due
to systematic barriers associated with conventional practice and clinical translational research. The work
in this presentation paints a different picture where surgery and intervention advancements no longer
represent fragmented injections of technology to advance focal capabilities. Rather, the assertion in this
talk is that technology treatment platforms of the future will be intentionally designed for the dual purpose
of treatment and discovery. As an exemplar, a platform technology is presented that translates complex
biophysical models represented by large systems of equations from predictive roles to ones that are
integrated to guide therapeutic applications such as tissue resection and locoregional intervention. The
work then goes on to suggest the use of quantitative, biomarker image-data driven forecasting as a means
to harness phenotypic presentation of disease for improving therapy application and potentially outcome.
Throughout the work, the common thread that ties the approaches together is the concept of biophysical
models serving as a constraining scaffold for sparse therapeutic & surgical/interventional data which when
of sufficient strength enables a functional purpose greater than the sum of contributing data. This blend of
model, therapy mechanism, phenotypic presentation, and therapeutic control as described typifies one
realization of these intraprocedural technology platforms designed for treatment and discovery. Finally, the
talk will conclude by looking at the impact on the field of biomedical engineering as well as paradigms being
investigated to codify training.
Speaker(s): Dr. Michael I. Miga, Ph.D. ,
Agenda:
Presentation by Prof. Miga followed by Q&A
Virtual: https://events.vtools.ieee.org/m/318468

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