Artificial Intelligence in Medical Imaging

Global Artificial Intelligence in Medical Imaging Market to Reach US$8.1 Billion by 2030

The global market for Artificial Intelligence in Medical Imaging estimated at US$1.5 Billion in the year 2024, is expected to reach US$8.1 Billion by 2030, growing at a CAGR of 32.9% over the analysis period 2024-2030. Deep Learning Technology, one of the segments analyzed in the report, is expected to record a 30.1% CAGR and reach US$4.2 Billion by the end of the analysis period. Growth in the Natural Language Processing (NLP) Technology segment is estimated at 36.8% CAGR over the analysis period.

The U.S. Market is Estimated at US$386.4 Million While China is Forecast to Grow at 31.4% CAGR

The Artificial Intelligence in Medical Imaging market in the U.S. is estimated at US$386.4 Million in the year 2024. China, the world`s second largest economy, is forecast to reach a projected market size of US$1.2 Billion by the year 2030 trailing a CAGR of 31.4% over the analysis period 2024-2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at a CAGR of 29.7% and 28.8% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 23.2% CAGR.

Global Artificial Intelligence in Medical Imaging Market - Key Trends & Drivers Summarized

How Is AI Revolutionizing Medical Imaging Diagnostics?

Artificial Intelligence (AI) is transforming medical imaging by enhancing diagnostic accuracy, streamlining workflows, and enabling early disease detection. Traditional imaging methods often rely on manual interpretation, which can be time-consuming and prone to variability. AI-powered systems address these challenges by analyzing imaging data with exceptional speed and precision, identifying abnormalities that might be missed by human eyes.

Machine learning algorithms trained on vast datasets of medical images can detect diseases such as cancer, cardiovascular conditions, and neurological disorders at an early stage. For instance, AI tools in radiology can analyze CT scans, MRIs, and X-rays to identify tumors, fractures, and other anomalies, reducing diagnostic errors and improving patient outcomes. These tools not only enhance the quality of care but also alleviate the workload of radiologists.

AI is also enabling advancements in personalized medicine by analyzing patient-specific imaging data to predict disease progression and response to treatments. This capability supports tailored therapeutic strategies, ensuring optimal care for individual patients. The integration of AI into medical imaging systems is thus redefining the standards of precision and efficiency in diagnostics.

What Drives the Adoption of AI in Medical Imaging?

The increasing prevalence of chronic diseases and the growing demand for early and accurate diagnostics are major drivers of AI adoption in medical imaging. Conditions such as cancer, cardiovascular diseases, and neurodegenerative disorders require timely detection for effective treatment. AI-powered imaging tools provide healthcare professionals with the insights needed to diagnose these diseases at earlier stages, improving patient outcomes and reducing healthcare costs.

The surge in imaging data generated by advanced diagnostic tools and electronic health records is another critical factor. AI systems analyze this data to uncover patterns and correlations, offering actionable insights that improve diagnostic accuracy. These capabilities are particularly valuable in large healthcare facilities, where radiologists often face overwhelming workloads.

Moreover, advancements in cloud computing and edge AI are making medical imaging solutions more accessible. These technologies enable healthcare providers to leverage AI-driven diagnostics without significant infrastructure investments, facilitating the adoption of AI tools across diverse healthcare settings, including rural and underserved areas.

Can AI Improve Efficiency and Accessibility in Medical Imaging?

AI is revolutionizing efficiency and accessibility in medical imaging by automating routine tasks and enabling remote diagnostics. AI-powered systems streamline workflows by automating image segmentation, annotation, and report generation, reducing the time radiologists spend on repetitive tasks. This efficiency allows radiologists to focus on complex cases and improves overall productivity in diagnostic imaging departments.

AI also enhances accessibility by supporting teleradiology and remote diagnostics. In areas with limited access to specialists, AI tools analyze medical images and generate diagnostic reports, bridging the gap in healthcare delivery. These capabilities are particularly beneficial in low-resource settings, where timely and accurate diagnostics can save lives.

Additionally, AI is enabling faster triage of emergency cases by prioritizing imaging studies that require immediate attention. For instance, AI systems can identify critical conditions such as strokes or pulmonary embolisms in real time, ensuring that patients receive prompt treatment. These advancements are transforming the delivery of medical imaging services, making them more efficient and accessible to a broader population.

What’s Driving the Growth of the AI in Medical Imaging Market?

The growth in the Artificial Intelligence in Medical Imaging market is driven by several key factors, reflecting its transformative potential in healthcare. The rising demand for precision diagnostics and personalized medicine is a significant growth driver. AI-powered imaging tools enhance diagnostic accuracy and enable tailored treatment plans, addressing the evolving needs of modern healthcare.

Technological advancements in AI, including deep learning and computer vision, are expanding the capabilities of medical imaging systems. These innovations improve the detection and characterization of diseases, making AI an indispensable tool for radiologists and clinicians. Furthermore, the increasing integration of AI with imaging modalities such as CT, MRI, and ultrasound is driving innovation in the field.

Regulatory support for AI-based medical devices and the growing focus on value-based care are also fueling market growth. Governments and healthcare organizations are encouraging the adoption of AI to improve patient outcomes and reduce costs. These factors, combined with the rising prevalence of chronic diseases and the continuous development of AI algorithms, are propelling the rapid growth of the AI in Medical Imaging market, positioning it as a cornerstone of future advancements in diagnostics and healthcare delivery.

SCOPE OF STUDY:

The report analyzes the Artificial Intelligence in Medical Imaging market in terms of units by the following Segments, and Geographic Regions/Countries:

Segments:
Technology (Deep Learning Technology, Natural Language Processing (NLP) Technology, Other Technologies); Modality (CT Scan Modality, MRI Modality, X-ray Modality, Ultrasound Modality, Nuclear Imaging Modality); Application (Neurology Application, Respiratory & Pulmonary Application, Orthopedics Application, Cardiology Application, Breast Screening Application, Other Applications); End-Use (Hospitals End-Use, Diagnostic Imaging Centers End-Use, Other End-Uses)

Geographic Regions/Countries:
World; United States; Canada; Japan; China; Europe (France; Germany; Italy; United Kingdom; and Rest of Europe); Asia-Pacific; Rest of World.

Select Competitors (Total 25 Featured) -

• Advanced Micro Devices, Inc.
• Butterfly Network, Inc.
• Canon Medical Systems USA, Inc.
• Digital Diagnostics
• EchoNous, Inc.
• Enlitic
• Exo Imaging, Inc.
• GE Healthcare
• Microsoft Corporation
• Tempus AI, Inc.

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