智慧成像开发平台市场报告：2031 年趋势、预测与竞争分析

全球智慧成像开发平台市场前景光明，在医疗保健、工业、农业和教育市场都蕴藏着巨大的机会。预计2025年至2031年期间，全球智慧成像开发平台市场的复合年增长率将达到14%。该市场的主要驱动力是对先进医学成像解决方案日益增长的需求，以及人工智慧和机器学习在成像技术中日益融合的趋势。

• 根据类型，Lucintel预测通用平台预计将在预测期内呈现高成长。
• 从应用角度来看，医疗领域预计将实现最高成长。
• 根据地区来看，预计亚太地区将在预测期内实现最高成长。

智慧影像开发平台市场新趋势

随着人工智慧、云端运算的进步以及工业领域对智慧视觉数据分析日益增长的需求，智慧成像开发平台市场正在快速发展。这些新兴趋势正在定义智慧成像解决方案建置和部署的未来。

• 低程式码/无程式码平台助力 AI影像处理普及：低程式码/无程式码智慧成像开发平台的兴起是一个显着趋势。低程式码/无程式码平台提供视觉化、直觉的介面和预先配置的建置模组，即使程式设计技能极少甚至完全没有程式设计技能的开发人员也能开发和部署基于 AI 的高级影像处理应用程式。这将推动 AI影像处理技术的普及化，降低非 AI 专家的进入门槛，促进快速原型製作，并在各行业中得到更广泛的应用。
• 边缘 AI 集成，实现即时处理：将 AI 功能直接嵌入边缘设备（摄影机、工业感测器、医疗设备等）进行即时智慧影像分析的趋势日益增长。开发平台提供工具和框架来优化 AI 模型，使其能够在资源有限的边缘硬体上部署，这种做法正变得越来越普遍。其优势包括更快的处理速度、更低的延迟、透过本地资料处理增强隐私保护，以及促进自主系统和工业自动化等应用中的即时决策。
• 联邦学习用于隐私保护模型训练：联邦学习正成为智慧成像开发的主要趋势之一，尤其是在医疗保健等隐私关键型应用中。这种方法允许从去中心化数据训练人工智慧模型，而无需暴露原始图像数据，从而保护患者隐私和数据安全。开发平台开始包含联邦学习框架和工具。因此，它有可能在不违反严格隐私法规的情况下，从去中心化资料建立强大的人工智慧模型，促进跨机构协作。
• 可解释人工智慧 (XAI) 建构信任与透明度：随着智慧成像系统在关键任务应用中的应用日益广泛，对人工智慧决策的透明度和可解释性的需求也日益增长。新平台包含可解释人工智慧 (XAI) 方法，可解释人工智慧模型产生特定预测的原因。这将增强人们对基于人工智慧的影像处理系统的信任度和课责，从而更好地理解和检验模型行为，尤其是在医疗保健和金融等受监管领域。
• 多模态资料融合，实现更深入的分析：如今，越来越多的平台将影像资料与其他模态资料（例如文字、感测器资料和时间序列资料）融合，以实现更全面、更深入的分析。开发平台为开发人员提供了整合、同步和整合不同资料流到人工智慧处理中的工具。其效果是，能够更深入地理解情境，在诊断和预测性维护等业务中实现更高的准确性，并透过整合互补的资讯来源，提升应对更复杂挑战的能力。

这些新趋势可望重塑智慧成像平台市场，提升人工智慧成像的可及性、效率、隐私保护、透明度和洞察力。低程式码/无程式码、边缘人工智慧、联邦学习、可伸缩人工智慧 (XAI) 和多模态资料融合的重视，正在向更多人开放高阶影像分析，并拓展其在各行各业的应用范围。

智慧影像开发平台市场的最新趋势

智慧视觉开发平台市场正在经历快速创新，专注于提高开发人员的生产力、优化模型性能以及简化智慧视觉解决方案的部署。

• 改进的预训练模型和模型库：最近的创新为特定的影像处理应用（例如，物件侦测、影像分割、分类等）提供了更先进、更多样化的预训练人工智慧模型。平台供应商还维护全面的模型库，以帮助开发人员利用现有模型并针对专门的应用进行调整，从而最大限度地减少训练时间和资源。
• 增强的资料註解工具和工作流程：高效有效的资料註解对于训练高效的AI模型至关重要。每个平台都提供了更强大的註释工具，包括自动标记支援、协作註释工作流程以及对多种註释类型（例如边界框、多边形、语义分割）的支援。这些增强功能使资料准备过程（AI开发中的一个主要瓶颈）更有效率。
• 简化的超参数调优和模型训练：开发平台正在添加更直觉的介面和自动化工具，用于超参数调优和模型训练。自动化机器学习 (Autum) 功能有助于发现最佳的模型架构和超参数，使开发人员能够更轻鬆地找到高效能模型，而无需手动试验。
• 灵活的部署选项和基础设施支援：该平台提供更灵活的部署选项，支援在云端基础设施、本地伺服器和边缘设备上部署，并改进与多种硬体加速器（GPU、TPU等）的集成，以提高各种部署环境中的模型推理性能。
• 广泛的 SDK 和 API 用于整合：智慧成像开发平台提供广泛的软体开发套件(SDK) 和应用程式介面 (API)，使开发人员能够轻鬆地将智慧成像功能融入他们的应用程式和工作流程中，从而实现与各种程式语言和开发环境的顺畅整合。

这些突破性技术可以加快开发週期，提高AI模型的效能和准确性，更容易在各种环境中部署，并且更容易将智慧成像功能整合到更多样化的应用中，从根本上改变智慧成像开发平台市场。

目录

第一章执行摘要

第二章全球智慧影像开发平台市场：市场动态

• 简介、背景和分类
• 供应链
• 产业驱动力与挑战

第三章市场趋势与预测分析（2019-2031）

• 宏观经济趋势（2019-2024）及预测（2025-2031）
• 全球智慧影像开发平台市场趋势（2019-2024）及预测（2025-2031）
• 全球智慧型影像开发平台市场（按类型）
  • 通用平台
  • 业界客製化平台
• 全球智慧型影像开发平台市场（按应用）
  • 医疗保健
  • 产业
  • 农业
  • 教育

第四章区域市场趋势与预测分析（2019-2031）

• 按地区
• 北美洲
• 欧洲
• 亚太地区
• 其他地区

第五章 竞争分析

• 产品系列分析
• 营运整合
• 波特五力分析

第六章 成长机会与策略分析

• 成长机会分析
  • 按类型
  • 按用途
  • 按地区
• 全球智慧影像开发平台市场的新趋势
• 战略分析
  • 新产品开发
  • 扩大全球智慧影像开发平台市场容量
  • 全球智慧成像开发平台市场的併购和合资企业
  • 认证和许可

第七章主要企业简介

• Siemens Healthineers
• GE Healthcare
• Philips Healthcare
• United Imaging Intelligence
• Infervision
• Deepwise
• SenseTime
• Megvii
• YITU Technology
• Hikvision

The future of the global intelligent imaging development platform market looks promising with opportunities in the medical, industrial, agriculture, and education markets. The global intelligent imaging development platform market is expected to grow with a CAGR of 14% from 2025 to 2031. The major drivers for this market are the rising demand for advanced medical imaging solutions, and the growing integration of AI & machine learning in imaging technologies.

• Lucintel forecasts that, within the type category, general platform is expected to witness higher growth over the forecast period.
• Within the application category, medical is expected to witness the highest growth.
• In terms of region, APAC is expected to witness the highest growth over the forecast period.

Emerging Trends in the Intelligent Imaging Development Platform Market

The intelligent imaging development platform market is rapidly evolving due to advances in artificial intelligence, cloud computing, and the expanding need for intelligent visual data analysis in industries. These emerging trends are defining the future of intelligent imaging solution building and deployment.

• Low-Code/No-Code Platforms for Democratizing AI Imaging: One prominent trend is the emergence of low-code/no-code intelligent imaging development platforms. Low-code/no-code platforms offer visual, intuitive interfaces and pre-configured building blocks that enable the development and deployment of advanced AI-based imaging applications by developers with minimal or no programming skills. The effect is democratization of AI imaging technology, facilitating quicker prototyping and broader adoption in multiple industries by lowering the entry obstacle for non-AI experts.
• Edge AI Integration for Real-Time Processing: Increasingly, there is a move toward bringing AI capabilities directly into edge devices (e.g., cameras, industrial sensors, medical equipment) for real-time intelligent image analysis. Development platforms are more commonly providing tools and frameworks to optimize AI models for deployment on resource-limited edge hardware. The effects include quicker processing speeds, lower latency, increased privacy through local processing of data, and the facilitation of real-time decision-making in applications such as autonomous systems and industrial automation.
• Federated Learning for Privacy-Preserving Model Training: Federated learning is becoming one of the main trends in intelligent imaging development, especially within privacy-critical applications such as healthcare. This method enables training AI models from decentralized data without exposing raw image data, maintaining patient privacy and data security. Development platforms are beginning to include federated learning frameworks and tools. The result is the possibility of constructing strong AI models from distributed data without violating strict privacy regulations and promoting collaboration among institutions.
• Explainable AI (XAI) for Building Trust and Transparency: As smart imaging systems are being used in mission-critical applications, the requirement for transparency and interpretability of AI decisions is increasing. New platforms are including Explainable AI (XAI) methods that offer explanations on why an AI model generated a specific prediction. The effect is greater trust and accountability in AI-based imaging systems, enabling enhanced understanding and verification of model behavior, particularly in regulated sectors such as healthcare and finance.
• Multimodal Data Fusion for More Insightful Analysis: There is an increasing trend towards platforms that enable fusion of imaging data with other modalities of data, including text, sensor data, and time-series data, to provide more holistic and insightful analysis. Development platforms are giving developers tools for integrating and synchronizing various streams of data into combined AI processing. The effects are richer context understanding, greater accuracy in operations such as diagnostics and predictive maintenance, and greater ability to handle more complex challenges by combining complementary sources of information.

These new trends in total are remaking the intelligent imaging development platform market by increasing access to AI imaging, its efficiency, privacy safeguards, transparency, and insights. The emphasis on low-code/no-code, edge AI, federated learning, XAI, and multimodal data fusion is opening advanced imaging analytics to wider audiences and broadening where they can be applied across industries.

Recent Developments in the Intelligent Imaging Development Platform Market

The intelligent imaging development platform market is seeing high-speed innovations centered on making developers more productive, optimizing model performance, and making intelligent imaging solutions deploy effortlessly.

• Pre-trained models and Model Zoos Improved: Latest advancements involve offering more advanced and varied pre-trained AI models for specific imaging applications (e.g., object detection, image segmentation, classification). Platform vendors also maintain comprehensive model zoos through which developers can take advantage of pre-existing models and tune them to specialized applications, minimally cutting training time and resources.
• Enhanced Data Annotation Tools and Workflows: Effective and efficient data annotation is important for training effective AI models. Platforms are providing better annotation tools with capabilities such as automated labeling support, collaborative annotation workflows, and support for multiple types of annotations (e.g., bounding boxes, polygons, semantic segmentation). These enhancements make the data preparation process more efficient, a major bottleneck in AI development.
• Hyperparameter Tuning and Model Training Simplified: Development platforms are adding more intuitive interfaces and automated tools for hyperparameter tuning and model training. Automated machine learning (Autum) features are making it simpler to discover best-performing model architectures and hyperparameters, so developers can find high-performing models more easily without manual trial and error.
• Flexible Deployment Options and Infrastructure Support: Platforms are providing more flexible deployment options and supporting deployment on cloud infrastructure, on-premise servers, and edge devices. They are also improving integration with multiple hardware accelerators (e.g., GPUs, TPUs) to improve model inference performance in different deployment environments.
• Extensive SDKs and APIs for Integration: Intelligent image development platforms are offering extensive Software Development Kits (SDKs) and Application Programming Interfaces (APIs) enabling developers to incorporate intelligent imaging features into their applications and workflows with ease. These enable smooth integration with a range of programming languages and development environments.

These breakthroughs are fundamentally transforming the intelligent imaging development platform market by speeding up the development cycle, enhancing the performance and accuracy of AI models, making deployment across various environments easier, and allowing for simpler integration of intelligent imaging functions into more varied applications.

Strategic Growth Opportunities in the Intelligent Imaging Development Platform Market

The intelligent imaging development platform market offers various strategic growth opportunities through its addressability of unique demands in several different application segments where intelligent image processing is rapidly emerging as an imperative necessity.

• Healthcare Diagnostics and Imaging: One of the most promising growth areas is delivering specialized platforms for medical image analysis, such as radiology, pathology, and ophthalmology. These platforms can provide pre-trained models for disease detection, segmentation tools for medical images, and compliance features for managing sensitive patient data, facilitating quicker and more accurate diagnoses.
• Automation and Industrial Quality Inspection: Smart imaging platforms can be customized for manufacturing sectors to automate visual inspection of quality, identify defects in products, and control robotic systems for automation. Opportunities for growth include offering software for integrating with industrial cameras, creating custom models for defect detection, and implementing robustness and reliability in adverse industrial environments.
• Security and Surveillance: There is a huge and increasing demand for intelligent video analytics in surveillance and security. Solutions that have features such as object detection, facial recognition, anomaly detection, and real-time event analysis have huge growth potential for improving situational awareness and enhancing security systems.
• Autonomous Vehicles and Robotics: Autonomous vehicle and robotics development is highly dependent on intelligent image processing for perception and navigation. Platforms that offer tools for sensor fusion, object tracking, scene understanding, and real-time processing on embedded systems have significant growth opportunities in this fast-growing market.
• Retail Analytics and Customer Experience: Intelligent imaging can be applied to retail for purposes such as product recognition, shelf monitoring, customer behavior analysis, and personalized recommendations. Opportunities for growth lie in creating platforms that are integrated with in-store cameras, offer real-time analytics dashboards, and improve the customer shopping experience.

These strategic growth areas point to the prospects of the intelligent imaging development platform market to grow by targeting the distinctive needs of healthcare, industrial automation, security, autonomous systems, and retail analytics. Platform customization and domain-specific tools and pre-trained models can open up enormous value and market share in these high-growth use cases.

Intelligent Imaging Development Platform Market Driver and Challenges

The intelligent imaging development platform market is driven by the convergence of advances in technology, the expanding demand for intelligent automation, and growing image data availability. Yet there are some challenges that must be overcome for its long-term and widespread adoption.

The factors responsible for driving the intelligent imaging development platform market include:

1. Growing Availability of Image Data: The advent of digital cameras, sensors, and the internet has resulted in an exponential growth in the amount of image and video data, giving rise to a huge requirement for tools that can analyze and extract useful insights from this visual data.

2. Developments in Artificial Intelligence and Machine Learning: Sustained advancements in AI and ML algorithms, especially deep learning, have dramatically enhanced the precision and functionality of intelligent imaging systems, creating demand for platforms that support their development and deployment.

3. Increasing Need for Automation Across Industries: Companies across industries are seeking to automate processes and tasks through intelligent imaging for enhanced efficiency, quality control, and cost savings.

4. Cloud Computing Infrastructure and Scalability: Access to scalable and strong cloud computing infrastructure offers the computational power and storage required to train and deploy sophisticated AI models for intelligent imaging applications.

5. Democratization of AI Development Tools: The introduction of easy-to-use development platforms and pre-trained models is bringing AI within reach of more developers and organizations, driving the pace of adoption of intelligent imaging technologies.

Challenges in the intelligent imaging development platform market are:

1. Data Annotation Bottleneck and Quality: Training effective AI models requires large amounts of accurately labeled image data. The process of annotating data can be cumbersome, costly, and error-prone, constituting a major bottleneck to developers.

2. Complexity of Model Development and Expertise Gap: Developing and tuning high-performing AI models for smart imaging tasks generally necessitates specialized machine learning expertise and knowledge, which can be an impediment for organizations lacking abundant AI skills.

3. Ethical Issues and Bias in AI Systems: Smart imaging systems may incidentally reinforce or exacerbate bias in the training data, thus resulting in unequal or discriminatory effects. Resolving ethical issues and guaranteeing equity and transparency in AI systems is a key issue.

The intelligent imaging development platform market is witnessing robust growth fueled by growing image data availability, AI/ML advancements, the need for automation, the scalability of cloud computing, and the democratization of AI tools. These factors are building a fertile ground for intelligent imaging solution development and adoption. But, data annotation bottlenecks challenges, model development complexity and expertise gap, and ethical issues surrounding bias in AI models must be addressed efficiently in order to guarantee the safe and widespread adoption of this revolutionary technology. Conquering these issues will be important to unleashing the full potential of the intelligent imaging development platform market.

List of Intelligent Imaging Development Platform Companies

Companies in the market compete on the basis of product quality offered. Major players in this market focus on expanding their manufacturing facilities, R&D investments, infrastructural development, and leverage integration opportunities across the value chain. With these strategies intelligent imaging development platform companies cater increasing demand, ensure competitive effectiveness, develop innovative products & technologies, reduce production costs, and expand their customer base. Some of the intelligent imaging development platform companies profiled in this report include-

• Siemens Healthineers
• GE Healthcare
• Philips Healthcare
• United Imaging Intelligence
• Infervision
• Deepwise
• SenseTime
• Megvii
• YITU Technology
• Hikvision

Intelligent Imaging Development Platform Market by Segment

The study includes a forecast for the global intelligent imaging development platform market by type, application, and region.

Intelligent Imaging Development Platform Market by Type [Value from 2019 to 2031]:

• General Platform
• Industry Customized Platform

Intelligent Imaging Development Platform Market by Application [Value from 2019 to 2031]:

• Medical
• Industrial
• Agriculture
• Education

Intelligent Imaging Development Platform Market by Region [Value from 2019 to 2031]:

• North America
• Europe
• Asia Pacific
• The Rest of the World

Country Wise Outlook for the Intelligent Imaging Development Platform Market

The intelligent imaging development platform market are characterized by increased demand for products that ease the process of integrating artificial intelligence and machine learning into imaging solutions. The platforms offer developers pre-configured functionalities, libraries, and APIs to speed up the development of intelligent imaging solutions in various industries such as healthcare, security, manufacturing, and autonomous vehicles. The emphasis is on democratizing access to sophisticated imaging analytics, allowing for quicker prototyping, and streamlining deployment of advanced image recognition, analysis, and interpretation capabilities. Cloud-based offerings and the access to vast datasets are also driving innovation in this rapidly evolving market.

• United States: The US market is experiencing heavy action in the space of intelligent imaging development platforms with high activity being driven by an active AI startup ecosystem and long-established technology titans. Latest trends and advances involve the proliferation of cloud-based platforms that provide integrated suites of tools for image annotation, model training, and deployment. Strong focus is given towards building platforms with industry-specific solutions, and this includes medical imaging and autonomous driving. Partnerships between research institutions and platform providers are also driving innovation.
• China: The market for China's intelligent imaging development platforms is growing very fast, driven by the government's vigorous promotion of AI implementation and enormous volumes of image data being created in a wide range of industries. Recent activities involve the appearance of a number of local platforms providing comparable functionality and inducing computer vision-related applications in security, intelligent cities, and industrial manufacturing. National independence in AI technologies is creating strong pressure for investing heavily in local platform development.
• Germany: Germany's strategy for the intelligent imaging development platform market is focused on industrial use and high-precision imaging. The focus has been on adapting AI to existing industrial systems for quality inspection, predictive maintenance, and automation. A strong focus on data privacy and security has resulted in the creation of platforms that are compliant with strict European regulations. Interactions between research institutions and industry partners are important for fueling innovation in this area.
• India: The market for intelligent imaging development platforms in India is in the growth stage, fueled by growing digitization in industries and a large pool of available AI talent. Recent trends are the appearance of local start-ups that provide AI-based imaging solutions and adoption of international platforms by Indian companies. The most significant areas of application are healthcare, agriculture, and security. Emphasis is on creating cost-effective and scalable solutions to meet the unique requirements of the Indian market.
• Japan: Japan's smart imaging development platform market is distinguished by high imaging quality and precision in industries such as manufacturing and healthcare. Advances recently have incorporated AI with the latest imaging hardware to improve diagnosis capabilities and simplify quality inspection routines. Reliability and safety play a significant part in driving developments, with developers seeking to develop highly tested and solid platforms. There is increased collaboration between industry, academia and government is fostering innovation in this market.

Features of the Global Intelligent Imaging Development Platform Market

Market Size Estimates: Intelligent imaging development platform market size estimation in terms of value ($B).

Trend and Forecast Analysis: Market trends (2019 to 2024) and forecast (2025 to 2031) by various segments and regions.

Segmentation Analysis: Intelligent imaging development platform market size by type, application, and region in terms of value ($B).

Regional Analysis: Intelligent imaging development platform market breakdown by North America, Europe, Asia Pacific, and Rest of the World.

Growth Opportunities: Analysis of growth opportunities in different type, application, and regions for the intelligent imaging development platform market.

Strategic Analysis: This includes M&A, new product development, and competitive landscape of the intelligent imaging development platform market.

Analysis of competitive intensity of the industry based on Porter's Five Forces model.

This report answers following 11 key questions:

• Q.1. What are some of the most promising, high-growth opportunities for the intelligent imaging development platform market by type (general platform and industry customized platform), application (medical, industrial, agriculture, and education), and region (North America, Europe, Asia Pacific, and the Rest of the World)?
• Q.2. Which segments will grow at a faster pace and why?
• Q.3. Which region will grow at a faster pace and why?
• Q.4. What are the key factors affecting market dynamics? What are the key challenges and business risks in this market?
• Q.5. What are the business risks and competitive threats in this market?
• Q.6. What are the emerging trends in this market and the reasons behind them?
• Q.7. What are some of the changing demands of customers in the market?
• Q.8. What are the new developments in the market? Which companies are leading these developments?
• Q.9. Who are the major players in this market? What strategic initiatives are key players pursuing for business growth?
• Q.10. What are some of the competing products in this market and how big of a threat do they pose for loss of market share by material or product substitution?
• Q.11. What M&A activity has occurred in the last 5 years and what has its impact been on the industry?

Table of Contents

1. Executive Summary

2. Global Intelligent Imaging Development Platform Market : Market Dynamics

• 2.1: Introduction, Background, and Classifications
• 2.2: Supply Chain
• 2.3: Industry Drivers and Challenges

3. Market Trends and Forecast Analysis from 2019 to 2031

• 3.1. Macroeconomic Trends (2019-2024) and Forecast (2025-2031)
• 3.2. Global Intelligent Imaging Development Platform Market Trends (2019-2024) and Forecast (2025-2031)
• 3.3: Global Intelligent Imaging Development Platform Market by Type
  • 3.3.1: General Platform
  • 3.3.2: Industry Customized Platform
• 3.4: Global Intelligent Imaging Development Platform Market by Application
  • 3.4.1: Medical
  • 3.4.2: Industrial
  • 3.4.3: Agriculture
  • 3.4.4: Education

4. Market Trends and Forecast Analysis by Region from 2019 to 2031

• 4.1: Global Intelligent Imaging Development Platform Market by Region
• 4.2: North American Intelligent Imaging Development Platform Market
  • 4.2.1: North American Market by Type: General Platform and Industry Customized Platform
  • 4.2.2: North American Market by Application: Medical, Industrial, Agriculture, and Education
• 4.3: European Intelligent Imaging Development Platform Market
  • 4.3.1: European Market by Type: General Platform and Industry Customized Platform
  • 4.3.2: European Market by Application: Medical, Industrial, Agriculture, and Education
• 4.4: APAC Intelligent Imaging Development Platform Market
  • 4.4.1: APAC Market by Type: General Platform and Industry Customized Platform
  • 4.4.2: APAC Market by Application: Medical, Industrial, Agriculture, and Education
• 4.5: ROW Intelligent Imaging Development Platform Market
  • 4.5.1: ROW Market by Type: General Platform and Industry Customized Platform
  • 4.5.2: ROW Market by Application: Medical, Industrial, Agriculture, and Education

5. Competitor Analysis

• 5.1: Product Portfolio Analysis
• 5.2: Operational Integration
• 5.3: Porter's Five Forces Analysis

6. Growth Opportunities and Strategic Analysis

• 6.1: Growth Opportunity Analysis
  • 6.1.1: Growth Opportunities for the Global Intelligent Imaging Development Platform Market by Type
  • 6.1.2: Growth Opportunities for the Global Intelligent Imaging Development Platform Market by Application
  • 6.1.3: Growth Opportunities for the Global Intelligent Imaging Development Platform Market by Region
• 6.2: Emerging Trends in the Global Intelligent Imaging Development Platform Market
• 6.3: Strategic Analysis
  • 6.3.1: New Product Development
  • 6.3.2: Capacity Expansion of the Global Intelligent Imaging Development Platform Market
  • 6.3.3: Mergers, Acquisitions, and Joint Ventures in the Global Intelligent Imaging Development Platform Market
  • 6.3.4: Certification and Licensing

7. Company Profiles of Leading Players

• 7.1: Siemens Healthineers
• 7.2: GE Healthcare
• 7.3: Philips Healthcare
• 7.4: United Imaging Intelligence
• 7.5: Infervision
• 7.6: Deepwise
• 7.7: SenseTime
• 7.8: Megvii
• 7.9: YITU Technology
• 7.10: Hikvision