How is AI Transforming Radiology Reporting?
Tools that reduce documentation burden without compromising clinical quality have become a priority for imaging centers managing higher case volumes with constrained staffing.
Last week, DeepHealth, a digital health subsidiary of RadNet, launched Reporting Pro, an AI-powered radiology reporting platform designed to reduce radiology documentation time and accelerate report delivery to referring physicians.
The company said that the platform combines speech recognition, AI-generated clinical findings, measurements, AI-generated impressions, quality assurance, and structured reporting into a single workflow. Reporting Pro was introduced at RSNA 2025 and is now commercially available in the United States and the United Kingdom, with plans to expand to Australia, South Africa, and select European markets by the end of the year, the company said.
“Radiology is entering a new era where AI supports the diagnostic journey from image analysis to reporting. Reporting Pro is a critical step forward, bringing intelligence into the reporting workflow so radiologists can focus on review and refinement, rather than manual documentation,” said Madhu Jahagirdar, Business and Product Leader, Enterprise Imaging, DeepHealth.
What the Platform Does
The company said that reporting remains one of the most time-intensive steps in the radiology workflow. Tools that reduce documentation burden without compromising clinical quality have become a priority for imaging centers managing higher case volumes with constrained staffing.
According to the company, Reporting Pro pulls in clinical AI findings and measurements from both DeepHealth's own FDA-cleared and CE-marked tools and compatible third-party AI systems, feeding them directly into structured report creation. The company said that It uses generative AI to organize findings and draft impressions, adapting over time based on physician feedback
The platform supports migration of existing templates and preferences from legacy reporting systems, allowing radiologists to retain familiar workflows while moving to an AI-native environment. It is compatible with any existing picture archiving and communication system (PACS) and radiology information system (RIS), according to the press release.
Reporting Pro is already being deployed across RadNet's network of outpatient imaging centers, providing scale validation of the platform in live clinical environments. The first external customers have been contracted, with deployments expected to go live within the next quarter, the company said.
The platform is available across all imaging modalities, including X-ray, ultrasound, CT, PET/CT, and MRI. When deployed alongside DeepHealth's Diagnostic Suite, Reporting Pro connects image management, AI findings, workflow orchestration, and reporting into a single environment.
Dr. Jason Sinner, Radiologist and Medical Director at RadNet, described the workflow change in practice. "With Reporting Pro, a structured report is already waiting when I open a case with findings populated, measurements in place and a preliminary report drafted. That significantly reduces reporting times, translating directly to faster turnaround times for patients and referring physicians who rely on receiving reports on a timely basis in order to make critical treatment decisions," Sinner said.
Key Takeaways
- DeepHealth launches Reporting Pro, an AI tool to streamline radiology documentation and enhance report delivery.
- The platform integrates speech recognition and AI findings to reduce documentation time in radiology workflows.
- Reporting Pro is now available in the US and UK, with plans for expansion to additional markets.
- The tool allows radiologists to maintain existing workflows while incorporating AI-driven efficiency into reporting.
- Generative AI adapts the reporting process based on physician feedback, improving accuracy and usability over time.