On the Role of Artificial Intelligence in Medical Imaging of COVID-19

Born, J.; Beymer, D.; Rajan, D.; Coy, A.; Mukherjee, V. V.; Manica, M.; Prasanna, P.; Ballah, D.; Shah, P. L.; Karteris, E.; Robertus, J. L.; Gabrani, M.; Rosen-Zvi, M.

During the COVID-19 pandemic, lung imaging takes a key role in addressing the magnified need of speed, cost, ubiquity and precision in medical care. The rise of artificial intelligence induced a quantum leap in medical imaging: AI has now proven equipollent to healthcare professionals in several diseases and the potential to save time, cost and increase coverage. But AI-accelerated medical imaging must still fully demonstrate its ability in remediating diseases such as COVID-19. We identify key use cases of lung imaging for COVID-19, comparing CT, X-Ray and ultrasound imaging from clinical and AI perspectives. We perform a systematic, manual survey of 197 related publications that reveals a disparity in the focus of the AI and clinical communities, caused by data availability and the lack of collaboration, and in modality trends, driven by ubiquity. Last, challenges in AI-acceleration and ways to remediate them are discussed and future research goals are identified.