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Optimized port placement for in vivo biosensors
Brady W King1, Luke A Reisner, R Darin Ellis
1Department of Electrical and Computer Engineering, Wayne State University, Detroit, MI 48202, USA. bwking@wayne.edu
Background:
We discuss the implementation of an automated port placement system for use with laparoscopic in vivo biosensors. Biosensors have physical limitations that make port placement crucial to proper data collection. The port placement process is prohibitively complex to execute optimally by human estimation.
Methods:
Port placement algorithms were integrated into an image-guided surgery system. Variables for optimization of ports include biosensor length, data collection restrictions, obstacles, and regions of interest. The port placement is applied to 3D virtual 'patients' created from medical imaging data. An example implementation for a Raman biosensor probe was created.
Results:
The prototype system can correctly find ideal port locations on a virtual patient based on biosensor limitations and regions of interest. Conversely, the system can evaluate and score an individual port selected by a user.
Conclusion:
As biosensors become incorporated into laparoscopic surgical environments, an automated port placement system would enable their optimized integration.
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