Medical Image Analysis Software Market Size, Share, Growth, Trends, and Global Industry Analysis: By Software Type (Integrated Software, Stand-alone Software), By Modality (Tomography, Ultrasound Imaging, Radiographic Imaging, Combined Modalities, Mammography), By Imaging Type (2D Imaging, 3D Imaging, 4D Imaging), By Application (Orthopaedic, Dental, Neurology, Cardiology, Oncology, Obstetrics & Gynecology, Mammography, Urology & Nephrology), By End Use (Hospitals, Diagnostic Centers, Ambulatory Surgical Centers, Others) and Region Forecast 2020-2031

Medical Image Analysis Software Market size was valued at US$ 3,750.0 million in 2024 and is expected to reach US$ 6,344.0 million by 2031, growing at a significant CAGR of 7.8% from 2025-2031. Moreover, the U.S. Medical Image Analysis Software Market is projected to grow at 8.2% over the forecast period. The market encompasses software solutions that acquire, process, quantify, and interpret medical imaging data (such as X-ray, CT, MRI, PET, and ultrasound) to support diagnosis, treatment planning, and clinical decision-making. These solutions include deterministic image-processing tools, advanced analytics, computer-aided detection/diagnosis (CAD), and AI/ML-driven algorithms that extract quantitative biomarkers, automate measurements, and integrate with PACS/EMR systems.

The market is experiencing rapid adoption driven by increasing imaging volumes, growing demand for diagnostic accuracy, and accelerated integration of artificial intelligence and deep-learning models that improve workflow efficiency and clinical outcomes. Key market dynamics include rising hospital IT modernization, regulatory scrutiny and reimbursement landscape evolution, segmentation by modality and application (oncology, cardiology, neurology), and strong growth in regions investing heavily in digital health infrastructure.

Facts & Figures

• The number of software as a medical devices (SaMD) approval by the U.S. Food and Drug Administration (FDA) increased from only 1 device in 2012 to 581 devices in 2021, reflecting a cumulative compound-annual growth rate of approximately 202.7% during that period.
• More than three-quarters (≈ 75%) of AI-enabled medical devices cleared by the FDA up to July 2023 are for radiology applications, and about two-thirds of those radiology devices obtained their marketing authorisation between August 2020 and July 2023.
• In the group of countries monitored by the Organisation for Economic Co operation and Development (OECD), the combined use of CT, MRI and PET diagnostic scanners in 2021 (or nearest year) exceeded 360 examinations per 1,000 population in countries such as the United States, Luxembourg, Korea, France and Austria.

Key Developments:

• In August 2025, Affidea Group entered a strategic partnership with Skin Analytics to deploy AI-based skin lesion assessment software (DERM) across European markets (starting Romania & Lithuania) thereby advancing use of image-analysis solutions in dermatology care pathways.
• In February 2025, Subtle Medical received clearance from the U.S. Food & Drug Administration (FDA) for its “Subtle HD” software, which can reduce MRI acquisition times by up to 80%.
• In July 2024, AI secured full certification under the EU’s Medical Device Regulation (MDR) for five of its medical-imaging AI algorithms, enabling expanded commercialisation of its image-analysis portfolio in Europe.

Medical Image Analysis Software Market Segmentation:

Based on the software type:

• Integrated Software
• Stand-alone Software

Integrated software is anticipated to lead the market, primarily driven by the growing demand for seamless interoperability and centralized workflow management across healthcare systems. Hospitals and diagnostic centers are increasingly prioritizing unified platforms that can integrate various imaging modalities—such as MRI, CT, PET, and ultrasound into a single analytical ecosystem. This integration minimizes data silos, enhances collaboration between radiologists and clinicians, and accelerates diagnosis and treatment planning. Integrated systems also allow direct connectivity with Picture Archiving and Communication Systems (PACS) and Electronic Health Records (EHR), enabling real-time data sharing and reducing manual errors.

Moreover, the rise of AI-driven analytics within these integrated environments enhances diagnostic precision while automating repetitive tasks. As healthcare providers shift toward enterprise-level digital infrastructure and value-based care models, the adoption of integrated image analysis solutions is expected to dominate due to their scalability, efficiency, and improved clinical outcomes.

Based on the modality:

• Tomography
  • Computed Tomography
  • Magnetic Resonance Imaging
  • Positron Emission Tomography
  • Single-Photon Emission Tomography
• Ultrasound Imaging
  • 2D
  • 3D&4D
  • Doppler
• Radiographic Imaging
• Combined Modalities
  • PET/MR
  • SPECT/CT
  • PET/MR
• Mammography

Tomography, particularly Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), is anticipated to dominate the market due to its widespread clinical adoption and advanced diagnostic capabilities. CT and MRI generate high-resolution, cross-sectional images that enable detailed visualization of anatomical structures, making them indispensable in oncology, cardiology, neurology, and orthopedic diagnostics. The growing global incidence of chronic and lifestyle-related diseases has driven the demand for precise, image-guided diagnosis and treatment planning.

Furthermore, advancements in AI-based image reconstruction, automated lesion detection, and 3D visualization tools have strengthened the use of tomography-based analysis software. Hospitals and diagnostic centers increasingly rely on CT and MRI analytics for early disease detection, radiomics, and quantitative imaging research. The integration of tomography data with deep-learning algorithms and cloud-based platforms enhances diagnostic accuracy and workflow efficiency, positioning tomography as the leading modality segment in the market.

Based on the imaging type:

• 2D Imaging
• 3D Imaging
• 4D Imaging

3D imaging is anticipated to lead the market owing to its superior capability to provide detailed volumetric visualization and quantitative assessment of anatomical structures. Unlike traditional 2D imaging, 3D imaging enables clinicians to examine tissues and organs from multiple perspectives, enhancing diagnostic precision in complex cases such as oncology, cardiology, and orthopedics. The growing demand for accurate treatment planning in surgical and radiotherapy applications has accelerated the adoption of 3D image analysis software.

Additionally, advancements in AI-based segmentation, image fusion, and rendering technologies have made 3D reconstruction faster and more accurate. The integration of 3D imaging with computer-aided diagnosis (CAD) tools also supports personalized treatment decisions and pre-surgical simulation. As healthcare systems move toward precision medicine and minimally invasive procedures, 3D imaging continues to gain prominence for its ability to deliver comprehensive, data-rich insights that improve clinical outcomes.

Based on the application:

• Orthopaedic
• Dental
• Neurology
• Cardiology
• Oncology
• Obstetrics & Gynecology
• Mammography
• Urology & Nephrology

Oncology is projected to remain the leading application segment in the market due to the growing global burden of cancer and the rising need for precise, image-guided diagnosis and treatment planning. Advanced imaging modalities such as CT, MRI, PET, and SPECT are extensively utilized in cancer detection, staging, and monitoring therapeutic response. Medical image analysis software enhances oncological imaging by enabling accurate tumor segmentation, volumetric assessment, and progression tracking through AI-assisted algorithms. The growing adoption of radiomics and quantitative imaging tools allows clinicians to extract valuable biomarkers for personalized therapy decisions.

Moreover, oncology-focused image analysis platforms are increasingly integrated into radiotherapy planning systems, improving treatment precision and patient outcomes. With continuous technological advancements and expanding use of AI for early cancer screening, the oncology segment continues to dominate the market, reinforcing its critical role in modern diagnostic imaging and precision oncology care.

Based on the end use:

• Hospitals
• Diagnostic Centers
• Ambulatory Surgical Centers (ASCs)
• Others

Hospitals are expected to dominate the market due to their high patient influx, advanced imaging infrastructure, and integration of multidisciplinary diagnostic workflows. Large hospitals often operate multiple imaging modalities such as CT, MRI, PET, and ultrasound requiring centralized and interoperable software solutions for efficient data management and analysis. The implementation of enterprise-level Picture Archiving and Communication Systems (PACS) and Electronic Health Records (EHR) has further strengthened the role of hospitals as major adopters of image analysis software. Hospitals also lead in deploying AI-driven imaging tools for disease detection, surgical planning, and treatment monitoring, significantly improving diagnostic accuracy and turnaround times.

Moreover, government initiatives promoting digital healthcare transformation and the adoption of cloud-based systems have accelerated hospital investments in imaging informatics. With their strong financial resources, trained personnel, and need for real-time collaboration, hospitals continue to represent the primary revenue-generating end-use segment in this market.