Radiology worklists built for urgency, not arrival time.
Founded in 2023 by a team who kept seeing the same problem in every reading room: the urgent case buried under routine scans, waiting its turn in the queue.
Radiology worklists are ordered by arrival time because that is how imaging systems were built in the 1990s. The clinical case for reordering by urgency has been obvious for decades. The technical barrier was never the idea. It was the implementation: getting a reliable urgency signal into the worklist in under sixty seconds, without touching the radiologist's workflow.
We built ImageAssist to close that gap. Our goal is not to automate radiology. It is to make sure the radiologist's clinical judgment is applied in the right order, starting with the cases that cannot wait. We believe that a decision-support tool that does one thing well, deploys without disruption, and earns radiologist trust over time is worth building. That is what we are doing.
Built by people who understand radiology operations.
Jonathan Sadlowe
CEO and Co-Founder
Previously led product for radiology workflow software at a major health IT company. Has worked directly with radiology operations directors at over 40 health systems. Saw the worklist prioritization problem from the operations side before building the technical solution.
Marcus Osei
CTO and Co-Founder
Machine learning engineer with a focus on medical imaging pipelines. Previously built DICOM processing infrastructure at a medical AI company. Designed the ImageAssist ingestion and scoring engine to operate within clinical latency requirements from day one.
Dr. Nadia Ferreiro
VP Clinical Affairs
Board-certified radiologist with a subspecialty in thoracic imaging. Leads clinical validation and radiologist engagement at ImageAssist. Her clinical perspective shapes both the AI model design and the criteria we use to define what counts as a correctly prioritized case.
Based in Boston. Focused on radiology.
ImageAssist was incorporated in 2023 in Boston. We are independently funded and have kept the company small and focused by design. We are not trying to build the platform for all of medical AI. We are building the tool that makes sure the urgent chest CT gets read before the routine follow-up.
Our clinical team works directly with radiology departments during deployment and stays engaged afterward. We measure our success by time-to-read on urgent cases at the institutions using our product, not by slide deck metrics.
If you want to talk to someone who will give you a straight answer about what ImageAssist does and does not do, contact us.
Contact
ImageAssist, Inc.
101 Merrimac Street, Suite 700
Boston, MA 02114
Work with us.
Whether you are a radiology department considering a pilot or a radiologist with questions about the clinical design, we want to hear from you.