Using customized computational analyses to evaluate the feasibility and risk of endoscopes with an SNR analysis as an example (Conference Presentation)

David Vega; Jennifer K. Barton

doi:10.1117/12.2561813

26 March 2020 Using customized computational analyses to evaluate the feasibility and risk of endoscopes with an SNR analysis as an example (Conference Presentation)

David Vega, Jennifer K. Barton

Author Affiliations +

Proceedings Volume 11231, Design and Quality for Biomedical Technologies XIII; 112310L (2020) https://doi.org/10.1117/12.2561813
Event: SPIE BiOS, 2020, San Francisco, California, United States

Abstract

Questions about the feasibility and risks of complex optical systems can be answered by ray-trace models evaluating the system performance. A problem is that these simulations require hours for each run, and months for a complete result. A solution is to automate the analysis using a programming language, but there remains the challenge of creating a ray-trace engine to perform the analysis. We instead utilize the Application Programming Interface (API) of existing ray-trace engines to perform many customized analyses. As an example, we computed an SNR map as a function of the field of view position of a forward scanning endoscope. The SNR was >20 at any field point. The origin of most noise was the uncoated cover plate and addressing the problem would increase the SNR to >40. Each ray-trace takes 2.7 hours representing several years to complete the analysis making it unpractical. The API code and a lower sampling for qualitative analysis reduced the required time by a factor of 1000x allowing for a reasonable workflow.

Conference Presentation

Citation Download Citation

David Vega and Jennifer K. Barton "Using customized computational analyses to evaluate the feasibility and risk of endoscopes with an SNR analysis as an example (Conference Presentation)", Proc. SPIE 11231, Design and Quality for Biomedical Technologies XIII, 112310L (26 March 2020); https://doi.org/10.1117/12.2561813

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