Digital and Intelligent Ultrasound: Redefining the Healthcare Ecosystem and Igniting B2B Growth

Industry trends: Ultrasound moves from standalone diagnosis to regional collaboration

China's healthcare sector is in a pivotal phase of high-quality growth. Guided by a national policy framework, the country is steadily advancing tiered diagnosis and treatment, examination result recognition, and compact medical community development. There is a shift in emphasis from individual hospital efficiency to efficient collaboration between major hospitals, primary care, and public health systems.

These developments have increased the importance of ultrasound imaging. As a non-invasive, real-time, portable, and cost-effective technology, ultrasound has become indispensable in clinical diagnosis and treatment, health screenings, maternal and child care, occupational health, early cancer detection, and primary public health. In integrated healthcare networks, lead hospitals are responsible for healthcare quality control, remote guidance, complex diagnoses, and training for primary institutions. These primary institutions, such as township health centers and community health service stations, handle initial screenings, common disease management, and follow-up care. A standardized and traceable cross-institutional smart ultrasound infrastructure is crucial for expanding access to high-quality medical resources to more communities.

However, significant challenges remain in ultrasound service supply and regional collaboration.

• Inconsistent quality standards hinder mutual recognition of examination results. Ultrasound diagnosis heavily relies on operator expertise. Institutions and practitioners differ in their techniques, standard sections, image quality, and report descriptions. Traditional manual spot checks have insufficient coverage and cannot meet the needs of hospital grading, regional quality control, medical insurance oversight, and region-wide result recognition.
• A shortage of primary healthcare professionals hampers diagnostic and treatment capacity. Training skilled ultrasound specialists is time-consuming. Primary institutions, health examination centers, and regional screening programs often face staff shortages, capability gaps, and heavy diagnostic workloads, which increase the risks of missed diagnoses, misdiagnoses, and inconsistent reports.
• Demand for screening is soaring, but service capacity cannot keep pace. There is growing demand for early cancer screening, public health examinations, maternal and child care, occupational health management, and chronic disease management. Traditional ultrasound models cannot support high-concurrency, standardized, and traceable screening. Medical institutions are under pressure to handle increased workloads with static resources.

The potential of digital and intelligent ultrasound extends beyond AI-assisted diagnosis in hospitals. It also involves developing long-term operational capabilities for regional quality control, primary screening, remote collaboration, and data governance, centered on medical communities.

MED Imaging AI's strategy: Working with carriers to streamline primary healthcare, cross-domain private networks, and sustainable operations

A leading healthcare tech firm, MED Imaging AI specializes in cutting-edge AI algorithms for medical big data. The company is dedicated to creating a real-time AI-driven expert system that can diagnose and treat diverse diseases using ultrasound imaging alongside an advanced AI bioinformatics analysis platform rooted in genomics. MED Imaging AI follows a three-pronged strategy of technological empowerment, in-depth application, and ecosystem collaboration to enable more effective use of AI in healthcare.

Technological empowerment: MED Imaging AI used Huawei's full-stack AI capabilities to build a technical foundation featuring Ascend computing power, medical foundation models, and cloud-edge-device synergy. The Ascend chip provides efficient and controllable computing power for real-time inference and massive data processing in ultrasound imaging. The proprietary medical multimodal foundation model integrates tens of millions of ultrasound images, clinical guidelines, and diagnosis and treatment standards. This enables image recognition, lesion segmentation, report generation, and quality control and review. The cloud-edge-device synergy architecture supports deployment in hospitals, medical communities, health examination centers, and primary public care, while ensuring real-time performance, data security, and cost-effectiveness.

In-depth application: MED Imaging AI focuses on the main service processes of ultrasound imaging. This solution improves the foundation of imaging through quality control, enhances efficiency through diagnosis, and expands scale through screening. Quality control ensures service consistency, AI-assisted diagnosis improves the efficiency and accuracy of diagnosis and treatment, and assisted screening and health examination expand the reach of inclusive healthcare services.

Ecosystem collaboration: MED Imaging AI is deepening its partnership with Huawei and establishing alliances with carriers for the large-scale implementation of digital and intelligent Ultrasound services. This collaboration goes beyond mere bandwidth, focusing instead on integrating AI applications, computing power, private networks, and local delivery for B2B settings like medical communities, primary care, and regional public health.

Why does MED Imaging AI partner with carriers? There are three main reasons. First, carriers can connect to local resources, including the national health commission, leading hospitals, primary healthcare institutions, and government and enterprise clients. With carrier support, the AI ultrasound solution can efficiently scale from single-hospital pilots to extensive implementation across the medical community and primary healthcare network. Second, carriers offer extensive, manageable, and operable 5G/5G-A networks, IP private networks, edge nodes, and data center resources. They can provide a reliable, secure, and low-latency computing network foundation for dynamic ultrasound image transmission, remote quality control, edge inference, and cloud-based review. Third, carriers offer government and enterprise project integration, O&M, billing and settlement, and sustainable operations. These capabilities help transform business models from one-time deliveries to sustainable subscription, leasing, and joint operations.

MED Imaging AI has worked with carriers and Huawei to create a model for ultrasound services. The model consists of one regional platform, three core capabilities, and many community nodes. The national health commission and top-tier hospitals lead the development of the regional platform, which serves as the service entry point. The three core capabilities are AI-powered quality control, AI-assisted diagnosis, and intelligent screening. Community nodes are deployed in township health centers, community health stations, health examination facilities, and other dedicated settings. Carriers provide private network slicing, edge cloud and computing access, government and enterprise outreach, community node integration, O&M assurance, and compliant transmission. Huawei supplies the computing power and cloud-edge-device technical foundation. MED Imaging AI delivers clinical algorithms, ultrasound AI products, quality control standards, and specific services.

The solution can be implemented flexibly through self-build or leasing, depending on the customer’s needs. For major hospitals and data-sensitive organizations, self-build and local deployment ensure data autonomy and efficient response. For regional public health institutions, integrated healthcare organizations, and primary screening, leasing the carrier cloud, edge nodes, or NPUaaS can reduce initial investment. Once the pilot matures, a sustainable operations model can be established by region, organization, or service volume.

Within one to two years, MED Imaging AI will deploy its digital and intelligent ultrasound solution in more than 100 benchmark hospitals, 90 regional medical institutions, and 40 chain health examination centers across China. This initiative will generate quantifiable value and set new industry standards. Within three to five years, MED Imaging AI aims to develop a comprehensive product lineup for every ultrasound setting and deploy its AI solution in over 200 Chinese cities. MED Imaging AI's long-term vision (beyond the next five years) is to develop industry standards for intelligent ultrasound imaging, streamline data throughout healthcare, health examination, and public health, and forge an AI-driven ultrasound healthcare service ecosystem.

Figure 1: Architecture of digital and intelligent primary ultrasound services supported by carrier 5G and computing-network convergence

Digital and intelligent ultrasound solution: An integrated AI platform for quality control, diagnosis, and screening

MED Imaging AI, in collaboration with top medical institutions, developed a digital ultrasound foundation model based on Huawei's ecosystem and officially released it in Guangzhou in February 2025. After nearly one year of clinical verification, the model has established an integrated AI-enabled platform for quality control, screening, and diagnosis. This platform, deployed on edge nodes and working in synergy with the carrier's low-latency network, enables real-time analysis of imaging data, immediate warning of quality issues, and cross-institutional process control.

MED Imaging AI has undergone a comprehensive intelligent upgrade, enhancing every step from scanning to diagnosis, and from single-point application to cross-regional collaboration.

• End-to-end smart quality control: During scanning, the system auto-warns about and corrects deviations from standards and protocols. It intelligently assesses image resolution and artifacts, filtering out subpar images. The system verifies report terminology, content, and logic to correct errors instantly. This ensures consistent diagnosis and treatment standards from start to finish.
• Precise diagnosis assistance: Trained on standard ultrasound and histopathological diagnosis (gold standard) data, the system can precisely locate, segment, and assess the benign or malignant status of lesions in the thyroid, breast, and cervical lymph nodes, informing clinical decisions and diagnostic accuracy.
• Efficient intelligent screening: The solution provides advanced lesion detection and classification for over 10 major organs to improve early identification of high-risk conditions. This greatly improves screening efficiency and quality standardization, paving the way for the large-scale implementation of inclusive screening.
• Quality control for regional collaboration: The quality control cloud platform balances medical resource distribution by using unified diagnostic standards for real-time uploads of primary care data, cloud-based data review, remote guidance, and result recognition.

This solution integrates AI throughout the entire ultrasound service process instead of relying on single-point algorithm identification. For doctors, the system offers real-time assistance in scanning, identification, report writing, and review. For hospitals, it accumulates quality control and research data to form a robust quality system. For medical communities, it extends leading hospitals' standards, capabilities, and services to primary institutions, ensuring regional service consistency.

Figure 2: Thyroid ultrasound AI-assisted diagnosis product ITS 200 and its system interface

Business practice: From single-hospital efficiency to regional medical community replication

This solution has been implemented in numerous hospitals and private examination organizations, creating diverse success stories ranging from improving hospital operational efficiency to expanding health examination capacity and cross-regional collaboration. Project results demonstrate an 80% increase in quality control efficiency for ultrasound screening, a 70% reduction in manual workloads, and 96.5% diagnostic accuracy. The solution has unified data management across different devices, bolstering scientific research with top-tier data. A single hospital can save over CNY3 million annually on quality control while enhancing diagnostics, treatment, and the patient experience.

In hospital applications, the solution streamlines medical technology, clinical care, and examinations. In assisted clinical diagnosis, MED Imaging AI focuses on major ultrasound departments. The service is now covered by Shanghai's medical insurance system, which ensures compliance and boosts its potential for broader application. In ultrasound examinations, AI helps doctors detect and classify lesions in the body and provides a health risk assessment model for personalized reports and intervention suggestions. In addition, the AI system is connected to the follow-up system to intelligently reach high-risk groups for timely intervention and proactive management.

In regional collaboration, MED Imaging AI established an integrated network spanning 10 municipal hospitals in Wuxi to seamlessly connect departmental quality control, point-of-care (POC) oversight, and remote collaboration. The system unified image quality evaluation standards and standardized operational processes in real-time applications like outpatient services and medical examination. Institutions are linked for data sharing. Higher-level hospitals offer quality control, expert diagnoses, and advanced technical support to primary-care facilities, improving the distribution of top-tier medical resources.

Figure 3: Collaborative architecture of the regional medical digital and intelligent ultrasound solution based on computing-network convergence

Digital and intelligent ultrasounds, which in the past were mostly procured by individual departments, are now being used to develop regional healthcare. For healthcare institutions, AI ultrasounds ensure standardized quality control, enhance diagnostic efficiency, expand screening capacity, and strengthen research data governance. For medical communities, platform-based capabilities unify standards, extend services to lower-level institutions, and improve primary diagnosis. For carriers, this presents an opportunity to transform from network suppliers to digital and intelligent healthcare service providers.

In the future, MED Imaging AI will continue to focus on AI-enabled ultrasound, collaborating with Huawei and carriers to offer a standard, replicable, and operable digital and intelligent ultrasound service system for hospitals, medical communities, health examination centers, and primary public health services. By drawing from AI, computing power, private networks, and applications, this service will not only revolutionize the ultrasound diagnosis and treatment process, but also serve as a new entry point for B2B growth in healthcare. This will enable tiered diagnosis and treatment and support the broader goals of accessible, high-quality healthcare across China.