Radiomics Market to Grow with a CAGR of 12.17% through 2030

The increasing demand for personalized medicine, along with significant advancements in imaging technologies, are major factors driving the growth of the Global Radiomics Market during the forecast period of 2026–2030.

According to TechSci Research report, “Global Radiomics Market – By Region, Competition, Forecast & Opportunities, 2030F”, the Global Radiomics Market stood at USD 15.35 Billion in 2024 and is anticipated to grow with a CAGR of 12.17% in the forecast period.

The global radiomics market is experiencing significant growth, driven by the increasing demand for personalized medicine and advancements in medical imaging technologies. Radiomics, which involves extracting quantitative data from standard imaging modalities like CT, MRI, and PET scans, offers critical insights into disease phenotypes, progression, and treatment responses. These imaging biomarkers, often imperceptible to the human eye, enable more accurate diagnoses, targeted therapies, and patient monitoring, aligning with the shift towards precision and value-based healthcare.

Technological advancements in imaging systems have enhanced image resolution, consistency, and reproducibility, providing a robust foundation for radiomics-based analysis. The integration of artificial intelligence (AI) and machine learning (ML) has further revolutionized radiomics workflows by automating feature extraction, improving pattern recognition, and facilitating faster, data-rich decision-making in clinical settings. AI-powered radiomics platforms utilize advanced ML models to analyze imaging data, segment regions of interest, and extract relevant features with high consistency, aiding clinicians in making informed decisions regarding diagnosis, treatment planning, and patient monitoring.

The rising prevalence of chronic diseases, particularly cardiovascular conditions, underscores the need for innovative diagnostic tools like radiomics. According to the Centers for Disease Control and Prevention (CDC), heart disease remains the leading cause of death in the United States, accounting for 702,880 deaths in 2022, which equates to one in every five deaths . Coronary artery disease (CAD) is the most common type, responsible for 371,506 deaths in the same year. Notably, about one in 20 adults aged 20 and older have CAD, and someone in the U.S. experiences a heart attack every 40 seconds . These statistics highlight the urgent need for enhanced diagnostic and monitoring tools, where radiomics can play a pivotal role.

However, the radiomics market faces challenges, including the lack of standardized imaging protocols, interoperability issues among platforms, and the complexity of integrating radiomics into routine clinical workflows. Variability in image acquisition parameters, such as slice thickness and contrast usage, can significantly alter the radiomic features extracted, creating challenges in comparing data across studies or validating radiomic models at scale. Additionally, the absence of universally accepted guidelines for image preprocessing, feature selection, and model validation further exacerbates these issues, hindering the development of regulatory-compliant, scalable radiomics solutions.

Ongoing innovations continue to accelerate adoption. Key trends include the expansion of radiomics applications beyond oncology into cardiology, neurology, and pulmonology, as well as the growing use of radiomic biomarkers in clinical trials to support drug development and treatment optimization. In cardiology, for instance, radiomics is used to assess myocardial tissue characteristics, detect fibrosis, and predict adverse cardiac events, offering valuable insights beyond traditional imaging interpretations. Similarly, in neurology, radiomics aids in the evaluation of brain disorders such as stroke and Alzheimer's disease by quantifying subtle changes in brain structure and function. This diversification expands the market potential for radiomics technologies, attracting investment from a wider range of healthcare sectors.

As medical imaging technology continues to improve and AI integration advances, the ability of radiomics to extract meaningful features across different organ systems and disease states strengthens. Radiomics is increasingly being recognized as a core component of the precision medicine ecosystem, offering scalable, non-invasive solutions that enhance clinical decision-making and improve patient outcomes across multiple therapeutic areas. As data-driven healthcare gains momentum globally, the market outlook for radiomics remains highly promising.                                                    

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The Global Radiomics Market is segmented into modality, image type, technology, application, regional distribution, and company.

The Deep Learning segment has emerged as the dominant technology within the global radiomics market due to its unparalleled ability to analyze complex, high-dimensional imaging data with high accuracy, speed, and scalability. Deep learning, a subset of machine learning based on artificial neural networks, excels at identifying subtle patterns and features in medical images that are often indiscernible to traditional analysis methods or even the human eye. This capability is crucial in radiomics, where extracting robust and reproducible quantitative features from imaging data forms the foundation of diagnostic and prognostic tools.

One of the primary advantages of deep learning is its end-to-end automation capability. Unlike traditional radiomics workflows that require manual image segmentation and feature engineering, deep learning algorithms can automatically perform these tasks with minimal human intervention. This not only accelerates the analysis process but also minimizes variability and human error, resulting in more consistent and reliable outputs.

Deep learning models are highly scalable and can learn from vast datasets, improving their predictive performance over time. As large, annotated imaging datasets become more available, deep learning systems can be trained to detect early signs of disease, stratify patient risk, and predict treatment responses across multiple conditions such as cancer, cardiovascular disease, and neurological disorders.

Deep learning also supports the integration of multimodal data—including imaging, genomic, and clinical information—thus enabling more holistic and personalized decision-making in healthcare. This aligns closely with the ongoing shift toward precision medicine.

The growing adoption of AI infrastructure in healthcare institutions, coupled with significant investments in AI-driven diagnostic tools, further cements deep learning’s position as the leading technology within the radiomics landscape. As regulatory bodies begin to approve more AI-enabled medical devices, deep learning's role in clinical radiomics applications is expected to expand rapidly, solidifying its dominance in the market.

Based on region, The Asia Pacific region has secured its position as the second-largest market for radiomics globally due to a combination of demographic, technological, and healthcare infrastructure developments that are driving rapid adoption of advanced imaging and AI-based diagnostic tools.

The region is witnessing a significant rise in the burden of chronic diseases such as cancer, cardiovascular disorders, and neurological conditions. With countries like China, India, and Japan reporting an increase in aging populations and lifestyle-related health issues, there is a growing demand for non-invasive, data-driven diagnostic technologies like radiomics to improve early disease detection and treatment personalization.

Governments across the region are actively investing in digital health initiatives and healthcare modernization. Countries such as South Korea, Singapore, and China are leading in AI research and the integration of AI technologies in healthcare systems. These nations are fostering public-private collaborations and offering funding support for innovations in medical imaging and radiomics, creating a conducive ecosystem for market growth.

The Asia Pacific region is home to many academic institutions, research organizations, and imaging centers that are increasingly engaging in radiomics research and clinical trials. This is helping accelerate technology validation, adoption, and commercialization.

The growing availability of affordable diagnostic imaging devices and the expansion of telemedicine in rural and semi-urban areas are enhancing access to radiomics-based tools. The region’s large patient pool, lower clinical trial costs, and increasing partnerships between AI companies and healthcare providers further solidify Asia Pacific’s position as a high-growth and strategically important market for radiomics solutions.

Major companies operating in Global Radiomics Market are:

• Radiomics.io (Computational Imaging & Bioinformatics Lab)
• Radiomics Bio
• Health Innovation Ventures (HIV)
• Sophia Genetics SA
• HealthMyne Inc
• Oncoradiomics
• ptTheragnostic BV

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“The global Radiomics market is experiencing strong growth driven by the rising demand for personalized and precision medicine, advancements in medical imaging technologies, and the increasing prevalence of chronic diseases such as cancer and cardiovascular disorders. The shift towards data-driven, non-invasive diagnostics has accelerated market adoption, with radiomics enabling deeper insights into disease characterization and treatment response. Key trends shaping the market include the integration of artificial intelligence and machine learning to enhance image analysis, expansion of applications beyond oncology into neurology and cardiology, and increased use of radiomics in clinical trials for drug development. Despite challenges such as lack of standardization, limited clinical workflow integration, and regulatory complexities, continuous innovation and growing healthcare investments support market momentum. Additionally, expanding healthcare infrastructure in emerging regions and the rising focus on value-based care further fuel growth, positioning radiomics as a critical technology in the evolution of precision healthcare worldwide.,” said Mr. Karan Chechi, Research Director of TechSci Research, a research-based management consulting firm.

“Radiomics Market - Global Industry Size, Share, Trends, Opportunity & Forecast, Segmented By Modality (Magnetic Resonance Imaging (MRI), Computed Tomography (CT), Positron-Emission-Tomography (PET), Others), By Image Type (2D v/s 3D), By Technology (Engineered Features v/s Deep Learning), By Application (Nuclear Medicine, Medical Imaging, Precision Medicine, Oncology, Others), By Region & Competition, 2020-2030F”, has evaluated the future growth potential of Global Radiomics 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 the Global Radiomics Market.

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