Artificial intelligence in the breast imaging market is one of the fastest-developing sectors based on growing demands for enhanced detection and diagnosis of breast cancer. Due to the continuously increasing incidence of breast cancer across the world, the demand for advanced imaging technologies also continues to rise.
AI technologies enhance diagnostic accuracy and speed in the case of breast cancer by integrating their AI algorithms into various imaging modalities and, therefore, presenting solutions to decrease false positives while increasing detection rates. Market leaders are heavily investing in Research and Development to innovate and advance their respective solutions for breast imaging. These advancements not only have a tendency to inflate the size of the market in concern but also solve the rising volumes of imaging data brought forth during screenings.
The emphasis on early detection of breast cancer favors the adoption of AI-powered solutions since such solutions offer clinicians valuable insight into breast abnormalities. Besides, some key players active in the artificial intelligence market are supportive through various partnerships and collaborations, which may encourage more holistic AI solutions for breast imaging.
The AI segment in breast imaging is likely to continue playing an increasingly important role in driving improvement in the care and treatment of patients as the market for breast imaging devices grows.
The US Artificial Intelligence in Breast Imaging Market
The US Artificial Intelligence in Breast Imaging Market is projected to be valued at USD 2,894.9 million in 2024. It is expected to witness subsequent growth in the upcoming period as it holds USD 27,609.0 million in 2033 at a CAGR of 28.5%. The U.S.
artificial intelligence in the breast imaging market is one of the leading countries concerning technological advancements, driven by rising awareness about breast cancer screening, coupled with improved access to healthcare services. Presently, the growth in the integration trend of AI technologies into traditional processes of imaging reflects the current market landscape, hence improving the accuracy of breast cancer detection.
Key milestones that have been witnessed during this period are the rise of AI-based solutions for breast imaging, driven by deep learning algorithms' power to efficiently analyze imaging data. Such solutions are meant to help radiologists effectively detect abnormalities within a breast, facilitating diagnosis. Growing investments from private and public sectors to support research initiatives have augmented innovation across the industry.
These factors have helped the market further grow, as the introduction of regulatory frameworks and guidelines by organizations like the FDA helped make people accept AI solutions in breast imaging. Moreover, with breast cancer becoming increasingly symptomatic, the demand for improved diagnostic methods is ever-changing the landscape of the breast imaging market.
On the back of the increasing adoption of AI technologies by healthcare providers in improving patient outcomes and screening processes, artificial intelligence in the breast imaging sector is therefore set to see strong growth.
Key Takeaways
- The Global Market Value: The Global Artificial Intelligence in Breast Imaging Market size is estimated to have a value of USD 7,913.1 million in 2024 and is expected to reach USD 85,443.3 million by the end of 2033.
- The US Market Value: The US Artificial Intelligence in Breast Imaging Market is projected to be valued at holds USD 27,609.0 million in 2033 from a base value of USD 2,894.9 million in 2024 at a CAGR of 28.5%.
- By Technology Segment Analysis: Machine Learning (ML) is projected to dominate the technology segment in this market with 39.1% of the market share in 2024.
- By Application Segment Analysis: Screening is anticipated to dominate this segment with 36.0% of the market share in 2024.
- Regional Analysis: North America is expected to have the largest market share in the Global Artificial Intelligence in Breast Imaging Market with a share of about 43.5% in 2024.
- Key Players: Some of the major key players in the Global Artificial Intelligence in Breast Imaging Market are Siemens Healthineers, GE Healthcare, Philips Healthcare, Hologic Inc., IBM Watson Health, Zebra Medical Vision, iCAD Inc., and many others
- Global Growth Rate: The market is growing at a CAGR of 30.4 percent over the forecasted period.
Use Cases
- Automated Breast Cancer Screening: AI reviews mammograms based on the identification of early-stage cancer, then assists radiologists in prioritizing urgent cases on time.
- Risk Assessment and Prediction: The conventional AI analyzes data from the patient to make personalized screening recommendations based on the presence of risk factors and genetic predisposition.
- Workflow Optimization in Radiology: AI automates routine tasks and smoothes the workflows in radiology, enabling the radiologist to focus on more complex cases of breast imaging.
- Integration with Other Health Data: AI integrates imaging and health records and provides comprehensive insights to ensure coordinated and better decisions in breast cancer care.
Market Dynamic
Trends
Integration of AI with Advanced Imaging ModalitiesAmong the main emerging trends in the AI in breast imaging market is the solid integration of AI algorithms with advanced imaging, such as three-dimensional mammography and MRI. This will enhance image analysis for better detection of abnormalities in the breast, further providing precise identification of cancerous tissues.
The integration of AI with these testing modalities automates diagnostic workflows and provides real-time analysis, thus offering early detection and treatment of breast cancer.
Adoption of AI-Powered Screening Programs
The adoption of AI-powered screening programs. Most of the healthcare systems have integrated AI into their respective national breast cancer screening programs to achieve a balance in the volume of work required by radiologists and reduce diagnostic errors that directly impact patient outcomes. AI-powered screenings can process large volumes of imaging data quickly while locating signs of the presence of breast cancer that are easily overlooked by human interpretation, therefore increasing the efficiency of large-scale screening programs.
Growth Drivers
Rising Incidence of Breast Cancer
With increasing cases of breast cancer globally, the demand has shifted towards ACBI solutions for initial-stage diagnosis and screening. As healthcare providers started giving substantial emphasis on early detection, which is the first line of treatment for the survival rate, AI technologies appeared in the scene. These AI solutions enhance the radiologist's ability to identify abnormalities more precisely and at a higher speed, which would further increase the growth of Artificial Intelligence in the breast imaging market.
Advancements in AI Algorithms
Advances in machine learning and deep learning technologies are considered one of the major driving factors for the AI market related to breast imaging. These enhance the ability of the AI system to analyze data in the case of breast imaging with greater accuracy and, consequently, lead to more accurate diagnoses of breast cancer. The more sophisticated the algorithms in AI become, the more subtle abnormalities will be picked up in the breast, and clinicians will have even more confidence in their use.
Growth Opportunities
AI Integration in Emerging Markets
The global artificial intelligence in the breast imaging market has significant potential in emerging markets by having a rise in the incidence of breast cancer along with access to diagnostic tools. AI-powered solutions for breast imaging will mean an affordable alternative for health systems in these regions during automation and enhancement of the diagnostic process. So, they have splendid opportunities for more growth, as more healthcare facilities want to adopt advanced imaging technologies..
AI-Driven Personalized Breast Cancer Treatment
The adoption of AI in breast imaging extends beyond diagnostics into personalized breast cancer treatment planning. This is made possible by healthcare providers who can offer personalized treatment planning through the use of AI technologies to analyze data specific to each patient about the nature of the detected cancer. Such a trend toward personalized care is foreseen to increase demand for AI-powered solutions in breast imaging and open new perspectives for market growth.
Restraints
High Initial Costs of AI Implementation
Probably the single most important stumbling block associated with the limitation of widespread adoption of AI in breast imaging is the high initial investment that needs to be undertaken for such implementation. This involves a much-needed updated investment by health care providers in new imaging systems, software, and training for radiologists, which is more often than not unaffordable, especially for smaller clinics or facilities in developing regions, and thus might slow the growth momentum of the market.
Concerns around AI Reliability and Data Privacy
While AI technologies hold considerable promise in the field of breast imaging, their reliability and tendency to commit mistakes raise questions. Thirdly, there is another concern related to privacy, since many image data are needed in training AI systems. Healthcare providers should handle the pressures of using imaging data, which raises a concern about the protection of patient data under strict regulations. Such issues may act as a damper on the large-scale adoption of AI in breast imaging.
Research Scope and Analysis
By Technology
Machine Learning (ML) is projected to dominate the technology segment in the artificial intelligence in breast imaging market as it will hold 39.1% of the market share in 2024. Machine learning is, in a fundamental way, changing how artificial intelligence is applied within the breast imaging market by making advanced, sophisticated tools available that help in building diagnostics of cancerous tissues in the breasts.
ML algorithms allow the system to learn from huge volumes of imaging data, a vital factor in increasing the accuracy of breast cancer detection. This increase in prevalence will drive demand for technologies that move faster, processing and analyzing big volumes of imaging data. It is one of the key reasons why it dominates this field, making improvements in the detection rate through premium pattern recognition.
ML algorithms can provide subtle anomaly detection in mammograms that may elude the human eye, significantly improving the efficiency of breast cancer screening. Therefore, as the breast imaging market is moving towards value and insights based on data analytics, the integration of ML technologies allows for better predictive analytics and earlier interventions, with overall better patient outcomes.
The continuous improvement in computing power and the increased capacity for data storage are creating new avenues for ML applications in breast imaging. Given that it can analyze voluminous data that is also complex, ML will continuously update its models to bring more accuracy and reliability in the diagnosis of abnormalities in the breast. Due to the growing interest from healthcare providers to use artificial intelligence solutions, the integration of machine learning into breast imaging technologies places it as a very key player in the fight against breast cancer.
By Application
Screening is anticipated to dominate the application segment the artificial intelligence in the breast imaging market with 36.0% of the market share in 2024. Applications related to screening dominate the artificial intelligence in the market of breast imaging as it is critically required for the early detection of breast cancer.
With increasing incidence, awareness about the importance of routine screening has increased significantly hence this application segment is highly vital for health care providers and patients. AI technologies offer a higher level of solutions that significantly improve screenings by providing far more accurate mammograms and other imaging modality assessments.
More focus is being placed on Ebola screening for breast cancer because of an increasing amount of evidence that shows the earlier the detection, the better the treatment outcome. Powered by AI, this tool analyzes imaging data quickly to pinpoint potential abnormalities that may require investigation. These technologies further ensure more accuracy in the detection of breast cancer by simplifying the process of screening and, finally, offer a better patient experience through reduced waiting times for diagnosis and less anxiety with diagnostic testing.
Moreover, healthcare providers are increasingly embracing AI solutions in radiology screening applications as a way of fine-tuning and streamlining workflow to improve productivity. By being able to provide preliminary assessments, radiologists can devote their time to more complicated cases, which in turn provides productivity enhancements in imaging departments.
Regarding this growth, the breast imaging market has and will continue to have a core focus on screening applications due to continued awareness and the need for proficient solutions in the fight against breast cancer.
By End-user
The dominant end-users of the artificial intelligence marketplace in breast imaging are hospitals and clinics because they play a very critical role in the diagnosis and treatment of breast cancer. It is worth noticing that these healthcare institutions increasingly adopt AI technologies to advance their diagnostic capabilities, streamline operations, and improve patient outcomes.
While the incidence of breast cancer is increasing, integration of AI solutions at the hospital level is one of the major priorities; this sort of solution helps in early and accurate diagnosis. Also, huge investment in sophisticated imaging technologies is considered another driving factor for the leading position of hospitals and clinics within the segment. Thus, many providers of health understand the integrations of AI-enabled solutions in breast images help them improve the rate of detection and workflow efficiencies.
This can help lighten the workload of the radiologists by utilizing AI algorithms in the analysis of the imaging data, hence promising to raise the quality of care for the patients undergoing screening and diagnosis. Besides, healthcare services being collaborative within the precincts of one's hospital or clinic facilitates this integrated approach to treating breast cancer.
AI can be integrated with EHRs and other health data systems in such a way it builds a more integrated patient-management framework. This makes it easier for healthcare providers to make recommendations based on comprehensive analyses of data; hence, driving the adoption of AI in breast imaging.
The breast imaging market will continue to focus much attention on hospitals and clinics as strategic end-users in the burgeoning market, befitting their critical role in response to the challenges associated with diagnosis and treatment related to breast cancer.
The Artificial Intelligence in Breast Imaging Market Report is segmented on the basis of the following
By Technology
- Machine Learning
- Deep Learning
- Computer-Aided Detection (CAD)
- Natural Language Processing
By Application
- Screening
- Diagnostics
- Risk Assessment
- Other Application
By End User
- Hospitals and Clinics
- Diagnostic Imaging Centers
- Breast Care Centers
- Other End Users
Regional Analysis
North America is expected to dominate artificial intelligence in the breast imaging market as it commands
43.5% of the total revenue in 2024. Various key factors prevail, and North America is likely to continue with the dominance in artificial intelligence in the breast imaging market, for the region possesses a strong healthcare infrastructure, the technology adoption is advanced, and huge investments are taking place in research and development.
The high incidence of breast cancer in the U.S. and Canada favors innovative screening and diagnostic solution demand, thus creating a fertile environment for AI-powered breast imaging technologies to bloom. Besides, leading healthcare institutions and tech companies nurture a very favorable environment for collaboration and innovation.
Integrating AI technologies with existing modes of imaging practices simplifies workflows and brings in enhanced diagnostic accuracy to facilitate healthcare providers becoming more productive in their operations. In addition, the emphasis on early diagnosis and personalized medicine fits with the capabilities of AI and will be an additional driver for AI growth in breast imaging.
The regulatory bodies in the region are also very encouraging towards such technological advances in healthcare and hence provide a very conducive landscape for AI solutions. This, in turn, induces the players operating within this space to be proactive about the rate at which they progress their offerings and get them across to the end user. As artificial intelligence in breast imaging market continues to evolve, North America's leading position will be maintained with technological innovation, healthcare investment, and a commitment to improving outcomes for patients.
Europe
- Germany
- The U.K.
- France
- Italy
- Russia
- Spain
- Benelux
- Nordic
- Rest of Europe
Asia-Pacific
- China
- Japan
- South Korea
- India
- ANZ
- ASEAN
- Rest of Asia-Pacific
Latin America
- Brazil
- Mexico
- Argentina
- Colombia
- Rest of Latin America
Middle East & Africa
- Saudi Arabia
- UAE
- South Africa
- Israel
- Egypt
- Rest of MEA
Competitive Landscape
The competitive scenario of the artificial intelligence in the breast imaging market comprises several players comprising established technology companies, healthcare providers, and innovative startups. Major companies in the market are doing enormous research and development to enhance their product offerings and maintain their viability in the market.
These may involve collaborative agreements and partnerships among stakeholders to integrate AI technologies into existing healthcare systems to advance the delivery of care for patients. Well-known firms within this space include GE Healthcare, Siemens Healthineers, and IBM Watson Health legacy players with deep experience in various imaging technologies that position them well to develop sophisticated AI approaches to the diagnosis of breast cancer. These companies have concentrated their efforts on developing user-friendly platforms that can connect easily with the conventional imaging modality, making transitions to AI-enhanced workflows easier.
Next to established players, various startups are also entering the market with innovative solutions for very specific needs in the domain of breast imaging. These companies are generally more agile and nimble regarding adaptation to emerging market demands so they can also introduce disruptive technologies that help challenge conventional approaches. This dynamic will further continue the evolution of AI in breast imaging toward achieving enhanced diagnostic performance and, by extension, better patient outcomes.
Some of the prominent players in the Global Artificial Intelligence in Breast Imaging Market are
- Siemens Healthineers
- GE Healthcare
- Philips Healthcare
- Hologic, Inc.
- IBM Watson Health
- Zebra Medical Vision
- iCAD, Inc.
- Aidoc
- Google Health
- RadNet, Inc.
- Qure.ai
- Fujifilm Medical Systems
- Other Key Players
Recent Developments
- April 2024: GE Healthcare introduced an AI platform in its mobile mammography truck, enhancing breast cancer detection and screening processes for precise, individualized patient care.
- April 2024: Siemens Healthineers received FDA clearance for its Mammomat B.brilliant system, offering ergonomic improvements, enhanced workflows, and automated positioning for improved patient comfort during mammograms.
- April 2024: Fujifilm announced its VISION2030 plan, targeting JPY3,100 million sales, investing in AI and technology areas like Bio-CDMO, potentially supporting AI in breast imaging advancements.
- March 2024: Toshiba launched an AI-enhanced breast imaging solution using deep learning algorithms, improving diagnostic accuracy and early-stage breast cancer detection for faster, more reliable diagnosis.
- January 2024: Gamma Medica upgraded its LumaGEM Molecular Breast Imaging system, improving AI algorithms for greater imaging accuracy and adding patient comfort features for dense breast tissue detection.
- December 2023: Toshiba announced a collaboration with an AI firm to integrate AI into breast imaging systems, focusing on risk assessment and personalized care for precision medicine advancements.
- November 2023: GE Healthcare launched the MyBreastAI suite, featuring three AI tools to enhance breast cancer detection accuracy, streamline image analysis, and reduce radiologist burnout through quicker evaluations.
- November 2023: Hologic showcased Genius AI Detection 2.0 at RSNA, improving breast cancer detection rates by reducing false positives by 70%, providing radiologists higher confidence in diagnostic accuracy.