3 March 2017 Using an Android application to assess registration strategies in open hepatic procedures: a planning and simulation tool
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Sparse surface digitization with an optically tracked stylus for use in an organ surface-based image-to-physical registration is an established approach for image-guided open liver surgery procedures. However, variability in sparse data collections during open hepatic procedures can produce disparity in registration alignments. In part, this variability arises from inconsistencies with the patterns and fidelity of collected intraoperative data. The liver lacks distinct landmarks and experiences considerable soft tissue deformation. Furthermore, data coverage of the organ is often incomplete or unevenly distributed. While more robust feature-based registration methodologies have been developed for image-guided liver surgery, it is still unclear how variation in sparse intraoperative data affects registration. In this work, we have developed an application to allow surgeons to study the performance of surface digitization patterns on registration. Given the intrinsic nature of soft-tissue, we incorporate realistic organ deformation when assessing fidelity of a rigid registration methodology. We report the construction of our application and preliminary registration results using four participants. Our preliminary results indicate that registration quality improves as users acquire more experience selecting patterns of sparse intraoperative surface data.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Derek J. Doss, Derek J. Doss, Jon S. Heiselman, Jon S. Heiselman, Jarrod A. Collins, Jarrod A. Collins, Jared A. Weis, Jared A. Weis, Logan W. Clements, Logan W. Clements, Sunil K. Geevarghese, Sunil K. Geevarghese, Michael I. Miga, Michael I. Miga, } "Using an Android application to assess registration strategies in open hepatic procedures: a planning and simulation tool", Proc. SPIE 10135, Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling, 101351Z (3 March 2017); doi: 10.1117/12.2255976; https://doi.org/10.1117/12.2255976

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