Technology Magazine reported on the availability of NVIDIA’s NV-Reason and NV-Generate models on HOPPR AI Foundry, enabling developers to train, evaluate, and fine-tune medical imaging AI with multimodal reasoning and synthetic data generation capabilities.

HOPPR announced that NVIDIA open models NV-Reason and NV-Generate are now available on the HOPPR™ AI Foundry, expanding developer access to advanced reasoning and generative AI capabilities for medical imaging development. Built on NVIDIA accelerated computing infrastructure, the Foundry provides a secure environment for building, evaluating, and fine-tuning imaging AI using foundation models, curated datasets, and traceable development workflows.

Written by Khan Siddiqui MD, this article explores how 2026 marks a turning point for AI in radiology, arguing for a shift from narrow point solutions toward integrated platforms that better support real-world clinical workflows.

Dr. Khan Siddiqui examines how rising imaging demand is driving radiologist burnout and explores how platform-based AI can help reduce workload and improve efficiency.

At RSNA 2025, speakers provide practical advice for advancing AI in radiology, focusing on real-world implementation, data governance, and clinical collaboration to move imaging AI initiatives forward.

At RSNA 2025, HOPPR launches two new programs for its AI Foundry, expanding access to expert support, foundation models, and curated datasets for medical imaging AI development.

HOPPR unveils its AI Foundry platform, designed to accelerate medical imaging AI development by providing foundation models, curated datasets, and integrated tooling for secure, compliant workflows.

HOPPR debuts its purpose-built platform for medical imaging AI at RSNA 2025, showcasing how the HOPPR AI Foundry provides foundation models, expert support, and secure tooling to accelerate responsible development of imaging AI solutions.

At RSNA 2025, HOPPR debuts its purpose-built AI development platform for medical imaging, showcasing how the HOPPR AI Foundry’s foundation models, expert support, and secure tooling help accelerate responsible imaging AI innovation.

HOPPR announces the launch of a Vision Transformer-based foundation model for 2D mammography that supports fine-tuning for imaging AI tasks including cancer detection and breast density classification, integrating easily into development workflows.

HOPPR announces the release of its 2D Mammography Foundation Model, a Vision Transformer-based model built to accelerate AI development in breast imaging. The model supports fine-tuning across diverse diagnostic tasks, empowering faster innovation in early detection and breast health.

Some firms, such as Aidoc, are working directly with the FDA. Others, such as HOPPR, are offering their foundation models for medtech companies to build their own AI tools.

TestDynamics has partnered with HOPPR to offer a secure development infrastructure for medical imaging within a quality management system, traceability of data provenance, and version control as part of its Satori AI Platform.

Imaging AI software developer HOPPR and TestDynamics have collaborated on the creation of an AI-based development infrastructure for medical imaging that can be incorporated into a quality management system.

The HOPPR Marie Curie Chest Radiography Model enables partners to fine-tune and deploy binary classifiers for chest X-ray images using their own data with API access, structured outputs, and usage billing. 

Backed by top-tier investors, HOPPR is scaling its secure platform for enabling developers and medical imaging vendors to build, refine, and deploy AI applications for medical imaging.