InSight Surgical Technologies LLC — Department of Health and Human Services SBIR Phase I: 393

Description

PROJECT SUMMARY ABSTRACTInSight Surgical TechnologiesLLCis a newly formed start up founded by senior members of a long standing NIH funded research effort to develop intraoperative image updating that maintains accurate image correspondence with the surgical field throughout a procedureThe effort has led to research innovations that have generated an intellectual propertyIPportfolio ofissued andpending patentsIn this Phase I SBIR applicationfeasibility of new algorithms for assembling multiple intraoperative stereovisioniSVacquisitions into a composite field of view and accomplishing iSV to MRI registration re registration will be developed along with conversion of existing iSV algorithms forD surface reconstruction and calibration in graphics processing unitGPUaccelerated formsSpecific aims willdevelop algorithms toiassimilate partially and or fully overlapping iSV acquisitions into a single field of viewandiiachieve iSV to preoperative MRIpMRregistration by incorporating closed cranium iSV to pMR alignment as an approximation for high fidelity intraoperative re registration post craniotomyimplement GPU versions of already optimized iSV calibration andD surface reconstruction software under quality systems in partnership with ArrayFire and prepare for GPU conversion of new software algorithms developed in Aimandevaluate Aimand Aimsoftware to show it meets accuracy attained with research grade codes or exceeds standard clinical methods using laboratory and clinical dataretrospectivelyand animal experimentsprospectivelySuccessful completion of Phase I will set the stage for Phase II during which new Aimalgorithms will join Aimcodes as finalized commercial grade GPU software under design controlvalidationprocedural use and quality systems sufficient for FDA regulatory filingaccompanied by similar generation of software for updated MRI viewsuMRMultisitemulti surgeon use data will be collected to establish clinically relevant and acceptable image updating platform performance in terms of ease of useefficiency and accuracy NarrativeFeasibility of developing graphics processing unitGPUbased intraoperative stereovisioniSValgorithms for calibrationD surface reconstruction and iSV to MRI image registration that are fast and accurate as core elements of an intraoperative image updating platform will be investigated