Tech-University Partnerships: The Case Study of FastMRI

Tech-University Partnerships: The Case Study of FastMRI

Almost two years ago, in November 2018, the artificial intelligence research program of Facebook, FAIR, announced that they started a joint research program with NYU School of Medicine’s Center for Advanced Imaging Innovation and Research (CAI2R). NYU and FAIR started sharing a standardized set of AI tools and MRI data to develop a fastMRI that aims to diminish the scanning time of MRI from an hour to minutes.

FastMRI is built on the premise that MRI scanning can require fewer measurement data to produce the image detail necessary for accurate detection of abnormalities thanks to in-depth learning modules that feed on previous MRI datasets. This means that the trained deep learning module can create accurate images from far less data. As a result, MRI scanning times can be reduced 10x through the use of big data sets. Building on 1.5 million MRI images drawn from 10,000 scans and raw measurement data from nearly 1,600 scans, NYU and FAIR developed a module that can forecast problematic MRI image areas faster than any module. Compiling the largest MRI dataset to date and making it open source, FAIR and NYU not only gather way in the field but also paves the way for further research and breakthroughs.

The primary purpose of the fastMRI project is to shorten scanning time, thus allowing more patients to benefit from the MRI technology. Further, fastMRI will enable patients who need immediate operations, such as the one with strokes and internal bleeding, to go through MRI, which would increase the success rate of surgeries.

fastMRI project is a significant case study to observe the advantages of building Knowledge Transfer Partnerships between technology companies and universities. Universities are the most significant knowledge powerhouses globally, and they can help technology companies climb faster in the growth ladder. Tech companies are the leading talent magnets of our time. Their human resources can not only give traction to university research projects but also add a competitive market edge to the outcome. Creating synergies between universities and tech companies quintessential because of the multiplying effect of joining two data and knowledge powerhouses’ efforts.

NYU and FAIR partnership offer a benchmark for future research in joint efforts between technology companies and universities, who are the most trendsetting and agile institutions of our time.

As Algomedicus, we would be thrilled to participate in joint research projects with universities in Turkey and abroad and allow our devoted data scientist team to share knowledge with renowned academics in their field. We believe in the power of collaboration and open sources to create the best outcome of future studies in artificial intelligence.