SBIR/STTR Research Award
Ultraportable Stroke CT Based on Stationary Carbon Nanotube X-ray Source and Deep Learning Image Formation
Award amount
$225,052Program and phase
SBIR · Phase IAward year
2019Award details
- Awarding agency
- Department of Health and Human Services
- Branch
- National Institutes of Health
- Recipient company
- ImagingX Inc.
- Proposal award date
- 2019-09-30
- Contract end date
- 2020-08-31
- UEI
- G3GDWBFAV2G1
- Solicitation number
- PA18-574
- Topic code
- 999
Research abstract
PROJECT SUMMARY The goal of thismonth SBIR phaseproject is developing an imaging device that will enable highly efficient and cost effective stroke imaging for patients suffered trauma eventsThe expected technical outcome will be a proof of concept head CT imaging system with subsecond imaging speedsub mSv radiation doseand high quality imagesImaging systems with such capabilities will address the current deficiency in timely diagnosis of stroke patientsand benefit society with higher efficiency and lower costSuch imaging device will make a strong economic impact on the global head CT imaging marketwhich is estimated to be about $billion in the U SIn a longer termthe novel imaging technology could be translated into markets for security screeningindustry inspectionand dental imagingThis project is based on the recent research results by DrCaoandapos s team under the support of an NSF CAREER awardPI DrCao$and a DrCaoandapos s Commonwealth Research Commercialization FundCRCFawardTitleComputed Tomography Without Moving Parts for Fast and Portable Biomedical Imaging$The project has a strong footing in intellectual propertyThe technology is protected by a few patent applications at the Virginia Techincluding USUltrafast Micro CT for Imaging Free Moving AnimalsInventorGuohua Caoand PCT USand USSystem and Method of Stationary Source Computed TomographyInventorGuohua CaoetalIn this projectthe team will design and build a proof of concept head CT platform to test the feasibility of ultraportable and compact head CT based on the stationary carbon nanotube x ray source design and deep learning image reconstruction algorithmThe expected outcomes from this project include demonstration of the feasibility for ultrafastlow doseand diagnostic imaging capabilities for intracerebral hemorrhage in head phantomsICHwith potential automatic ICH identification through deep learning algorithmA ready toprototype head CT device will be optimized and designedand a corresponding business plan will be developed PROJECT NARRATIVE Stroke is a common of death in the world at tremendous social and healthcare costsCurrently head CT is typically used for initial evaluation of stroke patients for signs of intracerebral hemorrhageAn ultraportable stroke CT that can be mounted in a small minivan would significantly shorten the time it takes for the diagnosis of intracerebral hemorrhageparticularly from trauma incidentsThis technology will save life and overall healthcare costs
Technology keywords
Not reported
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