#NVIEW MEDICAL SOFTWARE#
Follow best software development practices and maintain version control.Ĥ. Perform cutting edge low latency parallel computing, signal and image processing including data compression techniques.ģ. Development of 4D reconstruction and/or 4D visualization using C++ and CUDA.Ģ. Principal Job Duties and Responsibilities:ġ. They are expected to work and communicate well with other team members in order to meet the goals of the project and the company. This candidate will interact closely with University Professors as well as with nView’s staff to implement algorithms and develop high quality software that is at the forefront of low latency parallel computing in medical imaging. The role is very hands-on and will develop nView’s 4D reconstruction and visualization software. This candidate can derive creative solutions to software engineering problems. For the patient this translates intolonger recoveries - from days to weeks - and in many cases into a second revis.Īre you a self-starter who is motivated and driven? Do you thrive in a fast-paced startup environment? This candidate works as part of an experienced project team, contributing deliverables to a high impact project. In 4% to 11% ofthese surgeries, the implant placement is inaccurate. In spine surgery alone, there are more than 500,000procedures every year in the US utilizing implants such as screws. The broader impact/commercial potential of this project is the significant improvement ofsurgical accuracy, which will dramatically reduce surgical errors, improve outcomes andreduce healthcare costs. This research is readying the technology for clinical research, regulatory clearance and commercialization. Preliminary results show that these objectives are achievable. The clinical utility will be proven by building a system prototype and performing image quality and x-ray dose comparisons versus fluoroscopy and 3D in a realistic surgical setting. The clinical usability will be studied with an ergonomic model in a surgical setting. This Phase 2 project will I) prove the robustness of the reconstruction algorithm across a variety of use-cases, II) demonstrate the clinical usability of the 4D scanner, and III) confirm the clinical utility of the scanner. Phase 1 successfully demonstrated the feasibility of the reconstruction algorithm used by the proposed imaging modality by showing its potential of higher surgical accuracy in a single spinal screw insertion. This 4D technology has the potential to significantly reduce surgical inaccuracies, improve outcomes and reduce costs. This novel system will provide surgical imaging at a lower x-ray dose than fluoroscopy (current standard), with a geometry that allows concurrent imaging with surgery. This Small Business Innovation Research (SBIR) Phase 2 project will demonstrate a novel imaging modality, which provides near-real-time 3D live imaging - 4D - during surgery. The medical imaging technology being developed in this project has the potential to eliminate surgical inaccuracies across the $2.4B market of image guidance, improving clinical applications that range from orthopedic surgery to minimally invasive vascular interventions, to cancer diagnosis and treatments. For both the healthcare and economic systems these are avoidable costs.
The patient is non-productive, unable to carry out their daily routines for weeks, while the healthcare system has to absorb the costs of the longer recovery as well as the revision surgeries.
For the patient this translates into longer recoveries - from days to weeks - and in many cases into a second revision surgery. In 4% to 11% of these surgeries, the implant placement is inaccurate. In spine surgery alone, there are more than 500,000 procedures every year in the US utilizing implants such as screws. The broader impact/commercial potential of this project is the significant improvement of surgical accuracy, which will dramatically reduce surgical errors, improve outcomes and reduce healthcare costs. SBIR Phase II: 4D scanner for image guided interventions SBIR Award Abstract
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