The promise of AI in medical imaging is improved healthcare outcomes for both patients and providers through accelerated emergent condition identification, improved diagnoses, and better outcomes at lower costs. Many AI solutions can also
help to address physician workloads and associated burn-out.
TWO PRIMARY AI USE CASES FOR
MEDICAL IMAGING ARE:
Asynchronous AI, which describes devices that work “over” the image to perform its function separately from image acquisition (e.g., lung nodule detection), and
Integrated AI, which that performs concurrently with the same device that is capturing the image (e.g., iterative reconstruction algorithms).
Unfortunately, how AI is valued and reimbursed under the Medicare system is not conducive to fostering AI innovations. Current reimbursement systems are not designed to properly capture the value and cost of AI devices.