AI in Breast Imaging Market to Grow at 5.47% CAGR through 2030
Growing
prevalence of breast cancer, along with the rise in the adoption of digital
imaging technologies is expected to drive the Global AI In Breast Imaging
Market growth in the forecast period, 2026-2030.
According to
TechSci Research report, “AI In Breast Imaging Market – Global Industry
Size, Share, Trends, Competition, Forecast & Opportunities, 2020-2030F”,
the Global AI In Breast Imaging Market stood at USD 320.32 Million in 2024 and is
expected to reach USD 441.98 Million by 2030 with a CAGR of 5.47% during the
forecast period.
The Global AI
in Breast Imaging Market is undergoing a remarkable transformation, driven
by cutting-edge advancements in artificial intelligence (AI) and machine
learning (ML). AI technologies are reshaping how breast cancer is detected,
diagnosed, and monitored, offering unprecedented levels of precision, speed,
and accuracy in breast imaging. The application of deep learning algorithms,
particularly convolutional neural networks (CNNs), has played a pivotal role in
this revolution. These AI systems are trained to recognize patterns, anomalies,
and potential tumors in mammograms, ultrasounds, and MRIs, often with greater
accuracy than traditional methods.
One of the key
benefits of AI in breast imaging is its ability to detect subtle, early-stage
cancerous growths that might otherwise go unnoticed by human eyes. By enhancing
the sensitivity of imaging techniques, AI facilitates earlier detection, which
is crucial for effective treatment and improved patient outcomes. AI’s capacity
to reduce false positives and false negatives—common issues in traditional
mammography—has significantly improved diagnostic reliability. This reduction
in error rates is important because false positives can lead to unnecessary
biopsies, anxiety, and additional tests, while false negatives could delay
cancer treatment, allowing tumors to grow unchecked. AI-powered tools help
minimize these errors, enhancing diagnostic accuracy and streamlining
workflows. Another key area where AI is making a profound impact is in the
integration of advanced imaging technologies like 3D mammography (also
known as tomosynthesis) and digital breast tomosynthesis (DBT). Unlike
traditional 2D mammograms, 3D mammography captures multiple layers of breast
tissue, allowing radiologists to examine the breast in more detail, layer by
layer. This innovation is particularly valuable in dense breast tissue, where
tumors can often be obscured. AI algorithms can analyze 3D images more
efficiently than human radiologists, helping identify abnormal tissue and
lesions that may be missed during traditional 2D imaging. The synergy between
AI and 3D mammography improves diagnostic accuracy and provides more reliable
results for clinicians and patients alike.
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The integration
of AI with multimodal imaging, combining data from various sources such as
MRIs, ultrasounds, and mammograms, has further boosted its effectiveness in
breast cancer detection. This fusion of data allows AI to offer a more
comprehensive analysis by correlating information from multiple imaging
techniques, enabling a more thorough examination of potential tumors and
abnormalities. For instance, AI can combine data from mammography and
ultrasound images, providing a clearer, more holistic view of the breast tissue
and aiding in the precise localization and characterization of lesions. This
multimodal approach improves both the sensitivity and specificity of diagnostic
processes, leading to earlier detection and more accurate classification of lesions
as benign or malignant.
Beyond
diagnostic accuracy, AI has proven invaluable in reducing the workload of
radiologists. In many healthcare settings, there is a growing shortage of
radiologists, and AI can help address this by automating repetitive tasks, such
as the initial screening of mammograms and other imaging studies. AI algorithms
can process large volumes of data quickly, flagging potentially problematic
areas and allowing radiologists to focus on more complex cases or confirm
results. This capability is especially important in high-volume healthcare
settings, where the sheer number of imaging studies can overwhelm human staff.
By improving efficiency, AI can reduce delays in diagnosis, which is critical
in the early detection of breast cancer, where time is often of the essence.
The integration of AI into breast imaging also has a broader impact on
healthcare accessibility.
For instance,
AI-powered breast imaging solutions can be deployed in remote or underserved
regions, where access to trained radiologists and advanced imaging equipment
may be limited. With AI algorithms capable of providing accurate assessments of
imaging data, healthcare providers in these areas can still offer high-quality
diagnostic services, improving early detection rates and helping close the gap
in cancer diagnosis across various geographical regions. The growth of cloud-based
AI solutions has made it easier for healthcare providers to adopt these
technologies without the need for substantial upfront investment in hardware or
infrastructure. Cloud platforms allow healthcare systems to store, process, and
analyze vast amounts of imaging data remotely, providing scalability and
cost-effectiveness. Cloud-based AI services enable healthcare institutions,
even those in resource-limited settings, to integrate state-of-the-art
diagnostic tools into their practices without the heavy financial burden that comes
with purchasing expensive imaging hardware. As the technology advances, AI in
breast imaging is also moving toward personalized medicine. AI systems
are capable of analyzing patient data alongside imaging results, such as
genetic information, family history, and lifestyle factors, to help create a
more individualized diagnostic and treatment plan. For example, AI could assist
in identifying patients who are at higher risk of developing breast cancer
based on these factors, allowing for earlier screening and preventive measures
tailored to each patient’s unique profile. This move towards more personalized
care is not only improving the detection of breast cancer but is also helping
to optimize treatment plans based on a patient’s specific needs. Overall, the
growth of AI in breast imaging is transforming the landscape of breast cancer
detection, diagnosis, and treatment. Technological innovations, such as deep
learning algorithms, 3D mammography, and multimodal imaging, are significantly
enhancing the accuracy and efficiency of breast cancer screening. AI’s ability
to reduce errors, streamline workflows, and assist radiologists in high-volume
settings is making it an indispensable tool in modern healthcare. As the
technology continues to evolve and become more integrated into clinical
practice, the future of breast imaging holds great promise for improving
outcomes, reducing healthcare disparities, and ultimately saving lives.
The Global AI In
Breast Imaging Market is segmented into component, imaging modality,
application, end use, regional distribution.
Software is the fastest-growing segment in medical imaging, primarily due to its transformative impact on diagnostic accuracy. While both hardware and software are crucial for AI systems in breast imaging, software is the key driver behind the rapid growth of AI technologies. AI-powered software analyzes medical images, detects abnormalities, and provides valuable insights, enhancing breast cancer detection. By leveraging deep learning and machine learning, the software enables faster, more precise readings of mammograms, ultrasounds, and MRIs, identifying patterns that may be invisible to the human eye. Its ability to assist in early detection, reduce false positives, and improve diagnostic accuracy has made it indispensable in breast cancer screening. AI software seamlessly integrates with existing imaging systems, allowing healthcare facilities to adopt these technologies without overhauling hardware infrastructure. Radiologists can use it as a powerful tool within their current workflows, improving diagnostic confidence and overall efficiency.
Based on region,
Europe is the second dominant player in the Global AI in Breast
Imaging Market. Europe has established itself as a key market due to its
strong healthcare infrastructure, high adoption of advanced technologies, and a
growing emphasis on improving breast cancer detection and treatment. The region
is also known for its proactive approach to cancer screening and early
detection, which aligns well with the capabilities of AI in breast imaging. One
of the major factors contributing to Europe’s prominence in this market is the robust
healthcare systems found across many countries, particularly in nations
like the United Kingdom, Germany, France, and the Netherlands. These countries
have well-established screening programs and are increasingly integrating AI
tools into their breast imaging workflows. AI applications in breast cancer
detection are being adopted to improve diagnostic accuracy, reduce workloads on
radiologists, and address the rising incidence of breast cancer. European
countries are also highly invested in the development and testing of innovative
AI technologies, thanks to significant funding for medical research and public
health initiatives.
The regulatory
environment in Europe is another key factor driving the adoption of AI in
breast imaging. The European Union (EU) has been proactive in supporting
AI technologies in healthcare through policies such as the EU Medical Device
Regulation (MDR) and the General Data Protection Regulation (GDPR).
These regulations ensure that AI tools are safe, effective, and meet high
standards for patient data privacy. The EU's commitment to supporting digital
health and AI initiatives has helped establish Europe as a competitive player
in the market, with AI tools in breast imaging receiving regulatory approval
for use in various countries. The EU also invests heavily in collaborative
research projects involving AI in healthcare, further bolstering its position
in the global market.
Major companies
operating in Global AI In Breast Imaging Market are:
- Visage Imaging, Inc.
- CureMetrix, Inc.
- DeepHealth, Inc.
- GE HealthCare Technologies Inc.
- Hologic, Inc.
- Siemens Healthineers AG
- Fujifilm Holdings Corporation
- Koninklijke Philips N.V.
- iCAD, Inc.
- Medicalgorithmics SA
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“The future of
the Global AI in Breast Imaging Market looks promising, with significant
growth expected as AI technologies continue to evolve and integrate into
healthcare systems worldwide. Advancements in AI algorithms, particularly in
deep learning and image processing, will enhance diagnostic accuracy, reduce
false positives and negatives, and streamline workflows for healthcare
professionals. Increased adoption of AI in early breast cancer detection,
coupled with supportive regulatory frameworks, will drive its integration
across hospitals, clinics, and screening centers. The growing focus on
personalized medicine, improved patient outcomes, and the need for more
efficient diagnostic tools will further propel market expansion. As AI
continues to gain traction globally, it will revolutionize breast cancer
diagnosis, improving both accessibility and quality of care.,” said Mr. Karan
Chechi, Research Director of TechSci Research, a research-based management
consulting firm.
“AI In Breast Imaging Market - Global Industry Size,
Share, Trends, Opportunity, and Forecast, Segmented By Component (Hardware
and Software), By Imaging Modality (Mammography, Ultrasound Imaging, and MRI), By
Application (Screening, Diagnostics, and Image-guided Biopsy), By End Use
(Hospitals & Clinics, Diagnostic Imaging Centers, and Research Institutes),
By Region and Competition, 2020-2030F”, has evaluated
the future growth potential of Global AI In Breast Imaging Market and provides
statistics & information on market size, structure and future market
growth. The report intends to provide cutting-edge market intelligence and help
decision makers take sound investment decisions. Besides, the report also
identifies and analyzes the emerging trends along with essential drivers,
challenges, and opportunities in Global AI In Breast Imaging Market.
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