Radiology and Imaging AI
Algorithms that analyze medical images to flag findings, prioritize worklists, or support measurement and reporting.
Imaging was the first clinical domain to see broad algorithmic deployment, and it remains the category with the largest number of distinct products and the most established regulatory precedent.
Products in this category do meaningfully different jobs. Triage and notification tools reorder a worklist so a suspected finding is read sooner. Detection and characterization tools mark or measure a finding. Workflow and reporting tools sit around the read rather than inside it. A comparison that treats these as one category will compare products that were never alternatives to each other.
The buying chain runs through radiology leadership, imaging informatics, and the PACS team, with the decisive practical constraint usually being integration with the existing PACS and reporting environment rather than algorithm performance. See radiology AI comparison criteria.
5 companies
Listed alphabetically. This is not a ranking and inclusion is not an endorsement. Every record separates editorially compiled facts from vendor-stated claims, and no regulatory status is asserted. Editorial standards.
-
Aidoc
Medical imaging AI company offering algorithms across multiple imaging findings, distributed through a shared deployment platform.
-
Annalise.ai
Medical imaging AI company developing comprehensive findings-detection products for radiography and computed tomography.
-
Lunit
Medical AI company developing imaging analysis products, with published focus areas in chest radiography and mammography.
-
RapidAI
Medical imaging company focused on algorithms and workflow tooling for time-critical imaging, particularly stroke and vascular care.
-
Viz.ai
Medical imaging and care coordination company whose products detect suspected findings on imaging and notify a care team.