U.S. AI In Medical Imaging Market Size, Share & Trends Analysis Report By Technology (Deep Learning), By Application (Neurology), By Modality (MRI), By End Use (Hospitals), And Segment Forecasts, 2025 - 2030

Market Size & Trends

The U.S. AI in medical imaging market size was estimated at USD 524.42 million in 2024 and is expected to expand at a CAGR of 33.24% from 2025 to 2030. The surge in demand for managing extensive and complex datasets, coupled with government initiatives endorsing the integration of artificial intelligence-based technologies in healthcare, propels the adoption of artificial intelligence tools in the industry. A growing focus on alleviating the workload of radiologists has enhanced the utilization of artificial intelligence (AI) solutions to automate routine tasks and enhance diagnostic processes.

The market is witnessing increased financial backing from private players for AI-based start-ups, stimulating innovation and development in the sector. In addition, cross-industry collaborations and partnerships are rising as diverse sectors join forces to leverage artificial intelligence technologies in medical imaging, fostering partnerships and contributing to the market's overall growth. For instance, in May 2025, Philips partnered with NVIDIA to enhance MRI technology using AI. This collaboration aims to develop a foundational model that improves image quality, accelerates scan times, and streamlines diagnostic workflows.

“Our AI-powered MRI solutions are already enabling healthcare providers to deliver better care to more people. By partnering with NVIDIA to build an MR Foundational Model, we’re pioneering a new frontier for medical imaging, one that can potentially transform the role of MR in the diagnosis and treatment of a wide range of diseases. The benefits for patients and healthcare providers could be enormous.”

- Dr. Ioannis Panagiotelis, Business Leader of MRI at Philips

The growing need to handle large and complex medical datasets has led to an increase in the adoption of artificial intelligence in medical imaging in the U.S. This surge is driven by technology’s ability to enhance diagnostic precision, expedite image analysis, and improve overall healthcare efficiency through advanced data management and interpretation capabilities. For instance, Rayscape CXR differentiates between normal X-rays and those displaying anomalies, streamlining patient care and enabling rapid physician triage. With the capability to detect over 147 pathologies, it offers a swift and efficient method for doctors to prioritize and address patient needs.

Government initiatives in the U.S. supporting the integration of artificial intelligence in healthcare, particularly in medical imaging, have fueled significant advancements in the sector. These initiatives involve funding and regulatory support, fostering collaboration between the public and private sectors. The resulting acceleration of AI adoption in medical imaging has improved diagnostic accuracy, streamlined workflows, and enhanced patient care, propelling the market.

The National Institutes of Health (NIH) announced in September 2022 to invest USD 130 million over four years, subject to funding availability, to accelerate the widespread use of artificial intelligence in biomedical and behavioral research. The initiative, called Bridge2AI under the NIH Common Fund, brings together interdisciplinary teams to create AI-specific tools, resources, and detailed datasets to facilitate broader adoption of the technology in research communities. Moreover, the Food and Drug Administration (FDA) is actively formulating a regulatory framework for software modifications driven by AI/ML to establish pertinent guidelines ensuring safety and effectiveness.

Moreover, financial backing for AI-based startups is projected to propel the U.S. artificial intelligence (AI) in medical imaging market. For instance, in June 2023, Carta Healthcare, Inc., which is dedicated to enhancing patient care through clinical data, announced its Series B financing with an additional USD 25 million, boosted by investments from prominent health systems UnityPoint Health and Memorial Hermann Health System. This additional funding builds upon the initial USD 20 million series B financing announced in November 2022, featuring support from investors such as Asset Management Ventures and Frist Cressey Ventures.

Strategic Partnerships & Collaborations in the U.S. AI in Medical Imaging Market

Market Characteristics & Concentration

The chart below illustrates the relationship between industry concentration, industry characteristics, and industry participants. The x-axis represents the level of industry concentration, ranging from low to high. The y-axis represents various industry characteristics, including industry competition, level of partnerships & collaboration activities, degree of innovation, impact of regulations, and regional expansion. The U.S. AI in medical imaging market is fragmented, with several software and solution providers dominating the market. The degree of innovation, the level of merger & acquisition activities, and the impact of regulations on the industry are high. Moreover, the regional expansion of industry is moderate. 

The U.S. AI in medical imaging market experiences a high degree of innovation driven by technological advancements. The increasing adoption of artificial intelligence in clinical diagnostics and surgical planning supports innovations in the market. For instance, in March 2025, NVIDIA and GE HealthCare collaborated to enhance autonomous diagnostic imaging through Physical AI. This partnership focuses on developing autonomous X-ray and ultrasound technologies, utilizing the NVIDIA Isaac for Healthcare platform for simulation.

“We look forward to taking advantage of physical AI for autonomous imaging systems with NVIDIA technology to improve patient access and address the challenges of growing workloads and staffing shortages in healthcare.”

-Roland Rott, president and CEO of Imaging at GE HealthCare 

The market is also characterized by the leading players' high level of merger and acquisition (M&A) activity. This is due to the desire to gain a competitive advantage in the industry, enhance technological capabilities, and consolidate in a rapidly growing market. For instance, in January 2024, GE HealthCare announced an acquisition agreement with MIM Software from Cleveland, a global provider of medical imaging analysis and artificial intelligence solutions in molecular radiotherapy, radiation oncology, urology, and diagnostic imaging. The acquisition aims to integrate MIM Software's imaging analytics and digital workflow capabilities across diverse care areas, enhancing innovation and distinguishing GE HealthCare's solutions to positively impact patients and healthcare systems globally. 

The market is also subject to increasing regulatory scrutiny. This is due to concerns about the need to ensure patient safety, data privacy, and the reliability of artificial intelligence-driven diagnostic tools. As these technologies become integral to healthcare, regulatory agencies are actively addressing concerns related to validation, transparency, 

End user concentration in the market signifies the dominance of a limited number of healthcare providers or institutions in adopting AI technologies for diagnostic imaging. Various factors influence this concentration, including large healthcare systems with centralized decision-making and standardized technology implementations. For instance, in October 2023, Koninklijke Philips N.V. sought to improve prostate cancer care by implementing AI-enabled MR imaging. In contrast, Quibim's AI-enabled image analysis software was developed to aid clinicians in delivering faster and more accessible care for prostate cancer. The objective was to tackle staffing challenges and decrease the overall cost of healthcare. 

Case Study Insights: Enhancing MRI Analysis in Multiple Sclerosis with AI

Introduction

Multiple sclerosis (MS) is a complex neurological disorder characterized by diverse and often subtle changes in the brain and spinal cord. Magnetic Resonance Imaging (MRI) is crucial in diagnosing and monitoring MS. However, the interpretation of MRI scans is anticipated to be challenging due to the variability in lesion appearance and distribution. Recent advancements in Artificial Intelligence (AI) have shown promise in improving the accuracy and efficiency of MRI analysis in MS. A study published in Frontiers in Artificial Intelligence in April  2025 explores the role of AI in enhancing MRI analysis for MS patients.

Challenge

Traditional MRI analysis for MS relies heavily on manual interpretation by radiologists and neurologists. This process is time-consuming and subject to inter- and intra-observer variability, leading to lesion detection and measurement inconsistencies. Moreover, subtle changes in lesion load or new lesion formation are likely to be overlooked, potentially impacting treatment decisions and patient outcomes.

Solution

Incorporating AI, particularly machine learning and deep learning algorithms, into MRI analysis addresses several challenges. AI models trained on extensive datasets of MRI scans identify patterns associated with MS lesions. These models automate the detection and quantification of lesions, providing consistent and objective assessments. Furthermore, AI helps differentiate MS lesions from other abnormalities, improving diagnostic accuracy.

Result/Outcome

The application of AI in MRI analysis for MS has demonstrated several benefits:

• Increased Accuracy: AI algorithms have shown high sensitivity and specificity in detecting MS lesions, reducing the likelihood of missed or misidentified lesions.

• Efficiency: Automated analysis significantly reduces the time required for MRI interpretation, allowing quicker clinical decision-making.

• Consistency: AI provides standardized assessments, minimizing variability between different observers and over time.

• Enhanced Monitoring: AI tools can accurately track changes in lesion load over time, aiding in evaluating disease progression and treatment efficacy.

Technology Insights

Based on the technology, the deep learning segment held the largest share of 58.29% in 2024 as it is used in radiological applications such as image generation, object detection, image segmentation, and image transformation, this growth is attributed to the growing availability of extensive medical imaging datasets for training purposes facilitates the development of sophisticated deep learning models. For instance, in November 2023, OpenAI announced an initiative, OpenAI Data Partnerships, which collected records from various organizations to construct datasets for artificial intelligence training. The quality of the training files used directly impacts the reliability of the neural network built. A more pertinent dataset enables the neural network to respond to user queries more accurately. Creating a high-quality dataset is typically time-consuming and expensive, so OpenAI sought assistance from external organizations to streamline this effort.

The natural language processing (NLP) segment is expected to grow at the fastest CAGR over the forecast period. NLP technology utilizes a computer program that interprets and presents information in the current human language, encompassing text and images. Factors driving NLP are increased application in machine learning (ML) and artificial intelligence (AI). This expansion has led to new trends and developments, particularly in healthcare, where NLP plays a crucial role in tasks ranging from diagnosis to drug discovery. Integrating computer vision into NLP healthcare is noteworthy, as it aids in processing and interpreting complex medical images that may be challenging for humans to analyze accurately.

Application Insights

Based on application, the neurology segment held the largest revenue share of 37.46% in 2024, owing to the increased use of AI in neurology, as it provides better patient care and enables higher accuracy and higher efficiency. In addition, the technology is used in neuro-vascular disease detection, neuro-oncology, traumatic brain injury detection, and neurosurgery. For instance, in May 2023, TeraRecon launched Neuro Suite, an innovative clinical suite driven by artificial intelligence (AI). Tailored for disease triage and offering insights for differential diagnosis, Neuro Suite is specifically designed to facilitate care activation in neurological conditions like multiple sclerosis, neuro-oncology, and dementia. The platform offers seamless integration throughout the healthcare organization, addressing clinicians' challenges in decision-making for chronic neurological care. With its AI capabilities, Neuro Suite aims to enhance the efficiency and precision of diagnostic processes in neurological diseases. 

The breast screening segment is expected to grow at the fastest CAGR over the forecast period. The increasing incidence of breast cancer cases and the growing patient preference for early-stage detection, enabling prompt and precise treatment initiation, are significant drivers propelling the demand for breast screening. In addition, supportive government initiatives aimed at aiding clinical interpretation and expanding accessibility to breast cancer screening technologies are anticipated to be crucial factors fostering market growth.

These trends underscore a collective effort toward advancing breast cancer detection, diagnosis, and subsequent treatment, emphasizing the importance of proactive measures and accessible screening technologies. For instance, in November 2023, GE HealthCare announced MyBreastAI Suite, an innovative all-in-one platform comprising artificial intelligence (AI) applications to assist clinicians in breast cancer detection while enhancing workflow productivity. MyBreastAI Suite integrates three AI applications iCAD developed by iCAD: SecondLook for 2D Mammography, PowerLook Density Assessment, and ProFound AI for DBT. These applications collectively improve patient outcomes and early detection and aid radiology departments in enhancing operational efficiency.

Modalities Insights

Based on modalities, the CT scan segment held the largest market share of 34.86% in 2024 due to the higher standard imaging method for many clinical results. Both major and minor suppliers offer a wide variety of AI-based medical imaging solutions for use in the CT scan modality. The CT scan collects more thorough data than other methods. In addition, it has not been demonstrated that the small amounts of radiation used in CT scans are harmful over the long term. The market is segmented based on modality into MRI, CT scan, ultrasound, X-ray, and nuclear imaging. For instance, in November 2023, Brainomix, a company focused on developing AI-powered software solutions for precision medicine in stroke, lung fibrosis, and cancer, declared its ongoing expansion in the U.S. The company introduced its complete set of FDA-cleared modules within the Brainomix 360 platform, a comprehensive solution for stroke imaging. This platform aims to provide advanced capabilities for precise medical decision-making, particularly in stroke, offering healthcare professionals a robust tool for improved treatment decisions.

The X-ray segment is anticipated to expand at the fastest CAGR over the forecast period. The primary factor propelling this segment is the rising utilization of interventional X-ray equipment for surgeries guided by imaging, including C-arms and similar devices. The advancements in C-arm technology, particularly the emergence of compact C-arms equipped with flat panel detectors and digital radiography, have substantially heightened the global demand for X-rays. For instance, in October 2023, Koninklijke Philips N.V. introduced the Philips Image Guided Therapy Mobile C-arm System 3000, known as Zenition 30. These mobile C-arms are X-ray systems specifically designed to be utilized within the operating room, offering real-time image guidance for a diverse array of clinical procedures encompassing orthopedics, trauma, spine interventions, pain management, and various surgical processes.

End Use Insights

Based on the end use, the hospital held the largest share of 52.99% % in 2024 and is anticipated to grow at the fastest CAGR during the forecast period. The growth is anticipated as patients prefer hospitals for the treatment process in terms of convenience and various product offerings in one place.

The growing adoption of AI in medical imaging solutions, especially for cancer diagnostics, is impelling the segment's growth. Furthermore, hospitals partnering with the market players to deploy AI in medical imaging solutions is expected to drive market growth over the forecast period. For instance, in May 2022, Atlantic Health System and Aidoc partnered to implement an AI imaging solution to help physicians expedite care and enhance health outcomes.

Key U.S. Artificial Intelligence in Medical Imaging Company Insights

Some of the key players operating in the market include Microsoft Corporation, GE HealthCare, Canon Medical Systems USA, Inc., and Advanced Micro Devices, Inc. (AMD)

• Microsoft Corporation offers a wide range of AI capabilities and services, including computer vision, speech recognition, and language understanding. It also offers pre-trained models, SDKs, and APIs that help build AI-based workflows for various applications.

• GE HealthCare is one of the prominent companies integrating AI into medical imaging, leveraging cutting-edge technology to enhance diagnostic capabilities. The company has expertise in innovative AI solutions, such as the MyBreastAI suite, which aims to simplify radiologists' workflows and facilitate early detection of conditions like breast cancer.

TEMPUS, Butterfly Network, Inc., Digital Diagnostics Inc., and Viz.ai, Inc. are some other market participants in the U.S. AI in medical imaging market.

• Butterfly Network, Inc. is one of the prominent players in AI-driven medical imaging, specializing in handheld, pocket-sized ultrasound devices. Their innovative approach integrates AI to enhance diagnostic capabilities, making medical imaging more accessible and efficient for healthcare professionals across diverse settings.

• Digital Diagnostics Inc. is one of the pioneering companies in AI-driven medical imaging, focusing on developing advanced diagnostic tools. Their commitment involves leveraging artificial intelligence to enhance the accuracy and efficiency of medical imaging, ultimately improving diagnostic outcomes for various healthcare applications.

Key U.S. AI In Medical Imaging Company Insights

The U.S. AI in medical imaging market landscape is fragmented, with the presence of a small number of companies holding a majority stake. New expansion activities, product approvals, product launches, partnerships, and acquisitions have positively impacted the U.S. AI in medical imaging market in recent years. Furthermore, there has been a significant increase in the demand for AI in medical imaging due to the growing digitalization, which in turn is fueling the market growth.

Recent Developments

• In November 2024, Subtle Medical partnered with 626 to provide AI-powered imaging upgrades for MRI systems. Their collaboration aims to enhance image quality and significantly reduce scan times, enabling faster, more efficient MRI procedures.

"We are thrilled to partner with 626 to expand the reach of SubtleMR. Together, we're addressing a crucial need in the industry: providing healthcare facilities with cost-effective solutions that improve MRI efficiency and quality without requiring new, expensive scanner purchases."

- Josh Gurewitz, Chief Commercial Officer at Subtle Medical

• In November 2024, Canon Medical USA launched the Vantage Galan 3T/Supreme Edition, an AI-powered MRI system featuring Canon’s Altivity AI suite for optimized image quality and reduced scan times.

 “Our new real-time platform and AI-driven enhancements deliver high-quality imaging and operational efficiency, helping clinicians meet the diverse needs of patients and healthcare facilities today.”

-Mark Totina, Canon Medical’s magnetic resonance business unit director

• In November 2023, Koninklijke Philips N.V. expanded its enterprise imaging and introduced its HealthSuite Imaging AI solutions at RSNA23 on Amazon Web Services for faster adoption of new capabilities, improved operational efficiency, and enhanced patient care through secure cloud-based PACS, enabling high-speed remote access and AI-driven workflow orchestration.

• In November 2023, Canon Medical Systems introduced two out of four new computed tomography scanners, utilizing the upgraded Aquilion CT platform and incorporating artificial intelligence algorithms for improved image quality and simplified scanner workflows.

U.S. AI in Medical Imaging Market Report Scope

U.S. AI In Medical Imaging Market Report Segmentation

This report forecasts revenue growth at the country level and provides an analysis of the latest industry trends in each of the sub-segments from 2018 to 2030. For this study, Grand View Research has segmented the U.S. AI in medical imaging market based on technology, application, modalities, and end use:

• Technology Outlook (Revenue, USD Million, 2018 - 2030)

  • Deep Learning

  • Natural Language Processing (NLP)

  • Others

• Application Outlook (Revenue, USD Million, 2018 - 2030)

  • Neurology

  • Respiratory and Pulmonary

  • Cardiology

  • Breast Screening

  • Orthopedics

  • Others

• Modalities Outlook (Revenue, USD Million, 2018 - 2030)

  • CT Scan

  • MRI

  • X-rays

  • Ultrasound

  • Nuclear Imaging

• End Use Outlook (Revenue, USD Million, 2018 - 2030)

  • Hospitals

  • Diagnostic Imaging Centers

  • Others