DeepHealth unveiled an expanded portfolio of AI-powered imaging informatics and clinical AI solutions at RSNA 2025 in Chicago, marking a strategic evolution from RadNet’s diagnostic imaging business into a comprehensive health technology platform. The announcement encompasses new enterprise imaging infrastructure, clinical AI suites spanning five disease areas, and remote scanning capabilities designed to address fragmented workflows, strained radiology workforces, and inconsistent clinical outcomes across healthcare systems.
HotSpot Take:
When a diagnostic imaging operator integrates five clinical AI acquisitions into a unified platform within six months, it signals infrastructure consolidation accelerating faster than market adoption timelines.
The portfolio builds on RadNet’s July 2025 acquisition of iCAD and November 2025 acquisition of CIMAR UK, integrating breast cancer detection technology and cloud image management infrastructure into a unified platform called DeepHealth OS. According to the company, the integrated approach aims to unify previously siloed imaging tools, automate key workflow tasks, and orchestrate AI applications across the diagnostic imaging continuum.
“We are entering an era where AI-powered imaging can drive proactive, connected and more equitable care at global scale. By unifying clinical and operational intelligence into DeepHealth OS and deploying scalable infrastructure that accelerates adoption, our technology becomes a catalyst to stage shift disease, expand patient access, elevate care teams and enhance operational efficiency.” – Kees Wesdorp, President and CEO, DeepHealth
“We are entering an era where AI-powered imaging can drive proactive, connected and more equitable care at global scale,” said Kees Wesdorp, President and CEO of RadNet’s Digital Health Division, DeepHealth. “At DeepHealth, we harness AI in an integrated, end-to-end approach across our portfolio with the intent to improve healthcare delivery. By unifying clinical and operational intelligence into DeepHealth OS and deploying scalable infrastructure that accelerates adoption, our technology becomes a catalyst to stage shift disease, expand patient access, elevate care teams and enhance operational efficiency.”
Unified Imaging Infrastructure Through DeepHealth OS
At the core of the portfolio is DeepHealth OS, a cloud-native operating system that consolidates imaging informatics and AI capabilities into role-based experiences for radiologists, technologists, administrators, and referring physicians. The platform addresses technology fragmentation that has historically required healthcare organizations to manage multiple vendor relationships, integration projects, and data silos across PACS systems, specialty viewers, RIS platforms, and point AI solutions.
The Diagnostic Suite represents DeepHealth’s enterprise image management offering, delivering cloud and hybrid data management, ultra-fast streaming diagnostic viewing, AI-powered automated reporting, and integrated advanced visualization. The recent CIMAR UK acquisition brings additional cloud image management and interoperability capabilities, supporting expanded deployments across the UK and Europe. Components of Diagnostic Suite are actively deployed across RadNet sites and external customers, according to the company, reflecting capabilities to deliver impact at scale in both outpatient and teleradiology environments.
TechLive extends the infrastructure approach to remote scanning operations. The multimodality, vendor-agnostic solution provides remote imaging oversight across MR, ultrasound, CT, and PET/CT with 510(k) clearance. Deployment at RadNet to date has connected more than 400 scanners to TechLive, according to the company, with results showing 42% fewer MR room closures, driving higher throughput and improved patient and technologist experiences. TechLive is available as a standalone solution or through expanded collaboration with GE HealthCare for use with ultrasound products, and can be combined with Alpha RT remote-scanning technology with staffing and training expertise to support workforce and operational needs.
The Operations Suite expands beyond imaging interpretation to unify scheduling, registration, billing, analytics, and patient communication into a single cloud environment. The suite introduces patient engagement solutions designed to improve communication, scheduling, and adherence, along with agentic AI capabilities that enable automation to reduce administrative burden, optimize throughput, and improve system-wide coordination. Operations Suite is being deployed across RadNet and external customer sites. Current customers leveraging the legacy eRAD RIS will have options to transition to Operations Suite through updated functionalities.
Disease-Specific Clinical AI Suites
DeepHealth’s clinical AI portfolio spans five disease areas with expanded and new FDA clearances designed to stage shift disease, drive more timely screening and diagnostic pathways, and expand patient access.
Breast Cancer Detection and Diagnosis
The DeepHealth Breast Suite delivers what the company describes as one of the industry’s most comprehensive breast cancer detection and diagnostic offerings through modular interoperable applications covering detection, risk assessment, breast density measurement, workflow tools, and breast arterial calcification assessment currently in development. The suite builds on technology integrated through the iCAD acquisition to create an AI-powered, FDA-cleared end-to-end platform.
Breast Suite applications already support more than 10 million mammograms annually globally, according to the company. A large-scale real-world analysis of AI-powered breast cancer screening recently published in Nature Health demonstrated the effectiveness of applications within Breast Suite, showing a 21% increase in breast cancer detection rate across more than 579,000 women, with consistent benefits across dense-breast and diverse patient populations.
DeepHealth and GE HealthCare plan to expand their existing collaboration to include a wider suite of AI tools and extend access to the combined offering of mammography systems with DeepHealth Breast Suite worldwide.
Thyroid Imaging Automation
The Thyroid Suite integrates AI-powered modular applications into existing thyroid ultrasound workflows and technology, automating measurements and characterization while significantly improving workflow efficiency, according to the company. By automating nodule detection, characterization, and standardizing worksheets and reporting, Thyroid Suite applications help radiologists and sonographers work more efficiently and consistently.
Thyroid Suite builds on technology integrated through the See-Mode acquisition. Deployment across more than 200 sites within RadNet has demonstrated real-world impact, with radiologists interpreting more than 4,070 nodules accepting AI-based measurements and characterization without correction in greater than 94% of cases, according to company data. The solution supports all ultrasound manufacturers and is available standalone or through the recently announced partnership with GE HealthCare’s ultrasound imaging.
Neuroimaging Quantification
The Neuro Suite applications automate and standardize neuroimaging analysis through FDA-cleared applications including Brain Health for white matter hyperintensity detection and segmentation, and Brain Age for volumetric measurement. By automatically quantifying key structures including the hippocampus, lobes, and subcortical regions, Neuro Suite tracks longitudinal progression to support proactive care for conditions affecting brain structure and cognitive function.
Lung Cancer Screening
The expanded Chest Suite, previously referred to as DeepHealth Lung, automates pulmonary nodule detection, characterization, and volumetric quantification while standardizing reporting and longitudinal tracking. These automations support radiologists in identifying disease earlier and improving diagnostic accuracy, according to the company.
Chest Suite applications continue to enable population-scale screening programs worldwide, including NHS England’s Lung Cancer Screening Program. UK Government data show that 76% of detected cancers are now caught at earlier, more treatable stages, compared to only 29% historically. Applications within the Chest Suite are cleared in Europe and the UK and are currently US 510(k) pending, with plans to expand availability to US clinical sites.
Prostate MRI Interpretation
The next-generation Prostate Suite streamlines prostate MRI interpretation, analysis, and biopsy planning workflows. The suite integrates automated lesion detection and risk classification (510K pending), intelligent gland segmentation with PSA density calculation, and PI-RADS-compliant reporting into a single platform, delivering diagnostic accuracy and standardization of care, according to the company. From initial scan review to targeted biopsy handoff, the solution connects with more than nine fusion biopsy systems, eliminating manual data transfer while supporting radiologists at every step. The suite supports customer programs in the US and was recently selected for the TRANSFORM prostate screening trial in the UK.
AI Ecosystem Orchestration
AI Studio, developed in partnership with CARPL and RagaAI, unifies ecosystem AI solutions and enables seamless orchestration of applications directly within clinical workflow for automation and AI-powered care. AI Studio can integrate more than 140 AI algorithms from more than 75 ecosystem vendors, along with DeepHealth’s own clinical AI solutions, directly into the worklist, viewer, reporting, and workflow engine.
The system includes governance tools for AI evaluation, monitoring, and drift management in production, ensuring consistent performance and safe, reliable deployment at scale. This orchestration layer addresses a persistent challenge in radiology AI adoption: healthcare organizations have historically managed multiple point solutions with separate contracts, integration projects, and validation workflows, creating administrative overhead and limiting clinical utility.
Real-World Deployment and Clinical Validation
Elements of DeepHealth’s portfolio are already delivering impact for patients and healthcare providers globally, with more than 2,000 customers and more than 5,000 radiologists leveraging current solutions to deliver care, according to the company. The portfolio integration reflects RadNet’s acquisition strategy over the past year, combining organic development with strategic purchases of eRAD (radiology information and image management systems), Aidence (lung AI), Kheiron and iCAD (breast AI), Quantib (prostate and brain AI), See-Mode (thyroid and breast AI), and most recently CIMAR UK (cloud image management).
The consolidation creates both opportunities and integration challenges. Healthcare organizations benefit from simplified vendor management and unified workflows, but implementation complexity increases as organizations navigate migration paths from legacy systems, coordinate change management across multiple clinical departments, and validate AI performance within their specific patient populations and workflow contexts.
DeepHealth works with leading OEM, cloud, AI, and platform partners to unify previously fragmented tools into a connected, end-to-end imaging experience. The portfolio is presented in scientific sessions and at Booth 1329, South Hall, Level 3 at McCormick Place in Chicago, anchored by an Experience Theater featuring interactive educational sessions, live demonstrations, and panel discussions with clinical collaborators, technology partners, and research leaders sharing insights from real-world AI deployments.
Strategic Implications for Diagnostic Imaging
The DeepHealth portfolio announcement reflects broader market dynamics reshaping medical imaging. Traditional PACS and RIS vendors face pressure from cloud-native platforms offering integrated AI, advanced visualization, and workflow automation. Equipment manufacturers including GE HealthCare, Siemens Healthineers, and Philips increasingly embed AI directly in imaging systems while partnering with software platforms to deliver comprehensive solutions.
The RadNet strategy differs from traditional medical device manufacturers by leveraging operational insights from its 407 owned and operated outpatient imaging centers. This practice-based development model enables rapid testing and validation of new technologies in real-world clinical environments before broader commercialization, potentially accelerating product refinement and market adoption.
For healthcare organizations evaluating enterprise imaging strategies, the consolidation trend signals movement toward comprehensive platforms spanning image management, clinical AI, operations management, and patient engagement. Organizations must weigh the benefits of simplified vendor relationships and integrated workflows against dependencies on single-platform architectures and the complexities of migrating from legacy systems with established user bases and clinical validation.
The patient benefit potential centers on earlier disease detection through AI-enhanced screening programs, more consistent diagnostic accuracy through standardized interpretation tools, and expanded access through remote scanning capabilities that extend expert oversight to underserved areas. Realizing these benefits depends on successful integration across fragmented healthcare IT infrastructure, appropriate clinical validation within diverse patient populations, and sustainable change management that supports clinician adoption without introducing new workflow friction.
The broader healthcare system implications extend beyond radiology departments. As diagnostic imaging generates increasingly granular data on disease progression, tissue characteristics, and treatment response, imaging informatics platforms become foundational infrastructure for precision medicine initiatives, population health management programs, and value-based care models that depend on early intervention and longitudinal patient tracking.
– This original article was created with AI support.
