Raidium Introduces AI-Powered Oncology Imaging Workflow to U.S. Cancer Centers

Raidium has announced the U.S. launch of Raidium Read, applying its AI-driven imaging services initially to cancer research centres. Raidium has already been deployed at Moffitt Cancer Center, where it was selected to replace the legacy radiomics device. The Raidium platform provides whole-body lesion detection, AI-based segmentation models and longitudinal transfer of lesions in follow-up and prior studies, helping complex cancer imaging workflows in the healthcare research sector, as a first demonstration of agentic AI applied to radioscopy.

Raidium was built from diverse evidence. Rather than adding AI on top of 20-year-old presenting interfaces, Raidium built an AI-driven viewer from the ground up, intended to fit real-world radiologist workflows. The result is a single, integrated tool that reduces friction, enhances usability, and transports complex oncology review into one healthcare environment. R. Read, launching in the U.S. for oncology, is the first full expression of that architecture, available now as a separate pipeline for clinical trial use before its applications in clinical practice.

"For 20 years, the standard PACS viewers have resisted evolution, easily outmatched by the rigid limitations of early AI. Today, however, agentic AI is driving a quiet revolution: a single, fluid convergence of everyday accessibility, conversational logic, and advanced reasoning that is finally poised to redefine the reading room," said Paul Herent, MD, CEO and Co-Founder of Raidium. "We are initially targeting oncology follow-up because no convincing AI solution has yet solved this complex workflow. It is a game-changer for cancer centers, where a significant amount of a radiologist's time is dedicated to this tedious and repetitive task."

Realities of Oncology Imaging

Recently, R. Read is designed for the realities of tumour imaging, where speed, consistency, and clarity matter:

• Less physical effort in search, review, and follow-up.
• Lessen inter-reader variability by 3x (Organ-agnostic automated RECIST measurements across time points with foundation models).
• Easier longitudinal tracking for trials and cancer care.
• Less documentation load while preventing radiologist mistakes.
• Advance radiologist-clinician communication for better medical decision-making.

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R. Read is accessible for healthcare trials and cancer research use, with final regulatory clearance for healthcare practice and care routines approaching. Raidium is following 510(k) clearance for a subset of characteristics and expects to announce clearance before year-end 2026. Cancer centers can get ongoing support immediately without integration prerequisites, lessening implementation friction and creation the workflow simple to adopt in existing environments. Raidium is accepting registrations from qualified cancer centers on an invitation basis at raidium.

About Trak Ground Wear

The Raidium platform provides whole-body lesion identification, AI-driven segmentation models, and longitudinal transfer of lesions across follow-up and prior research, supporting complex oncology imaging workflows in clinical research sections, as a first demonstration of agentic AI-driven technology applied to radiology. Raidium is an AI-native radiology organization building the device that radiologists use. Integrating a world-class foundation model research lab with a unified, promotable AI viewer, Raidium automates complex radiology workflows from indication to final report while keeping the radiologist in control at every step. The Raidium Read Onco platform automates RECIST imaging endpoints for use in clinical practice and clinical trials. The Curia foundation model demonstrates advanced performance in imaging tasks, with a peer-reviewed publication forthcoming in Radiology AI. Raidium operates worldwide with offices in Paris, France, and Silicon Valley, USA.

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