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¼¼°èÀÇ ¶óµð¿À¹Í½º ½ÃÀå - »ê¾÷ ±Ô¸ð, Á¡À¯À², µ¿Çâ, ±âȸ, ¿¹Ãø, ¸ð´Þ¸®Æ¼º°, À̹ÌÁö À¯Çüº°, ±â¼úº°, ¿ëµµº°, Áö¿ªº°, °æÀï½ÃÀ庰(2020-2030³â)Radiomics Market - Global Industry Size, Share, Trends, Opportunity & Forecast, Segmented By Modality, By Image Type, By Technology, By Application, By Region & Competition, 2020-2030F |
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¿¹Ãø ±â°£ | 2026-2030³â |
½ÃÀå ±Ô¸ð : 2024³â | 153¾ï 5,000¸¸ ´Þ·¯ |
½ÃÀå ±Ô¸ð : 2030³â | 306¾ï 4,000¸¸ ´Þ·¯ |
CAGR 2025-2030³â | 12.17% |
±Þ¼ºÀå ºÎ¹® | Àڱ⠰ø¸í À̹Ì¡(MRI) |
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Radiomics market was valued at USD 15.35 Billion in 2024 and is expected to reach USD 30.64 Billion by 2030 with a CAGR of 12.17%. The global radiomics market is witnessing significant growth, fueled by the increasing adoption of precision medicine and the integration of advanced analytics in medical imaging. Key market drivers include the rising prevalence of chronic diseases such as cancer and cardiovascular conditions, growing demand for non-invasive diagnostic tools, and technological advancements in imaging and artificial intelligence (AI). According to the 2022 GLOBOCAN, there were nearly 20 million new cancer cases and 9.7 million cancer deaths worldwide. Lung cancer was the most frequently diagnosed, accounting for 12.4% of all cases, and was also the leading cause of cancer death, responsible for 18.7% of cancer-related deaths. The report projects that by 2050, annual new cancer cases will reach 35 million, a 77% increase from 2022, highlighting the urgent need for enhanced global cancer control measures. Radiomics plays a pivotal role in extracting quantitative features from standard medical images, offering deeper insights into disease characterization, prognosis, and treatment response.
Market Overview | |
---|---|
Forecast Period | 2026-2030 |
Market Size 2024 | USD 15.35 Billion |
Market Size 2030 | USD 30.64 Billion |
CAGR 2025-2030 | 12.17% |
Fastest Growing Segment | Magnetic Resonance Imaging (MRI) |
Largest Market | North America |
However, the market faces certain challenges, including the lack of standardized protocols for radiomic data acquisition and analysis, limited interoperability between imaging platforms, and concerns regarding data privacy and regulatory compliance. Additionally, the complexity of radiomics workflows and the need for multidisciplinary expertise can hinder broader clinical adoption.
Emerging trends shaping the market include the integration of radiomics into clinical decision support systems, increasing collaboration between imaging software vendors and AI solution providers, and the incorporation of radiomic biomarkers in clinical trials for drug development and personalized treatment strategies. Academic and research institutions are also contributing to innovation by expanding the applications of radiomics beyond oncology to neurology, cardiology, and inflammatory diseases.
The impact of COVID-19 initially disrupted imaging procedures and clinical workflows; however, the pandemic ultimately underscored the value of remote diagnostics, big data analytics, and non-contact screening tools. This shift accelerated interest in radiomics as a key enabler of virtual health technologies and AI-assisted diagnostics, positioning it as a cornerstone in the evolution of modern, data-driven healthcare systems.
Key Market Drivers
Rising Demand for Personalized and Precision Medicine
The rising demand for personalized and precision medicine is a significant driver fueling the growth of the global radiomics market. As cancer and other complex diseases continue to impact millions worldwide, nearly 10 million cancer-related deaths occurred in 2020 alone, healthcare systems are shifting toward more individualized, data-driven treatment strategies. Personalized medicine tailors' medical treatment to the individual characteristics of each patient, and radiomics plays a critical role in enabling this transformation by extracting vast amounts of quantitative data from medical images such as CT, MRI, and PET scans.
These imaging biomarkers provide deep insights into tumor phenotype, tissue heterogeneity, and disease progression, which are often undetectable by the human eye. This capability is vital in oncology, where radiomics helps identify tumor subtypes, predict therapeutic responses, and monitor treatment outcomes in a non-invasive manner. The advent of targeted therapies and immunotherapies has made such precise tools indispensable for effective patient stratification.
Radiomics also complements traditional diagnostics by offering additional layers of information, while its integration with genomic and clinical data-termed radiogenomics-enables a more comprehensive understanding of disease biology. Furthermore, pharmaceutical companies increasingly use radiomics in clinical trials to optimize patient selection and improve drug efficacy. As global healthcare moves toward precision and value-based care, the demand for radiomics as a tool for personalized medicine is expected to surge significantly.
Key Market Challenges
Lack of Standardization
One of the most significant challenges hindering the growth of the global radiomics market is the lack of standardization across various stages of the radiomics workflow. Radiomics involves the extraction of quantitative features from medical images, and for these features to be clinically meaningful and reproducible, consistent imaging protocols are essential. However, there is currently a high degree of variability in how imaging data is acquired, processed, and analyzed across different healthcare institutions, scanner types, software platforms, and even operators.
Differences in image acquisition parameters-such as slice thickness, contrast usage, resolution, and scanning protocols-can significantly alter the radiomic features extracted, even when analyzing the same patient or pathology. This inconsistency creates challenges in comparing data across studies or validating radiomic models at scale. As a result, findings that appear promising in research setting often fail to translate into real-world clinical practice, limiting the trust of healthcare professionals in adopting radiomics-based tools.
The lack of universally accepted guidelines or standards for image preprocessing, feature selection, and model validation further exacerbates the issue. This fragmented landscape hinders the development of regulatory-compliant, scalable radiomics solutions that can be used confidently in multi-institutional trials or integrated into electronic health records (EHRs).
Key Market Trends
Integration of Artificial Intelligence and Machine Learning
The integration of Artificial Intelligence (AI) and Machine Learning (ML) technologies is revolutionizing the global radiomics market by significantly enhancing the accuracy, efficiency, and clinical utility of radiomic analysis. Radiomics involves extracting vast amounts of quantitative data from medical images, which can be complex and time-consuming to analyze manually. AI and ML algorithms automate and optimize this process, enabling faster and more precise identification of patterns and features that may be imperceptible to the human eye.
AI-powered radiomics platforms utilize advanced machine learning models to analyze imaging data, segment regions of interest, and extract relevant features with high consistency. These models can learn from large datasets, improving their predictive performance over time. By integrating AI, radiomics shifts from a primarily descriptive approach to a predictive and prognostic tool, aiding clinicians in making informed decisions regarding diagnosis, treatment planning, and patient monitoring.
Moreover, AI facilitates the integration of multimodal data, combining imaging, genomic, clinical, and pathological information, to deliver a holistic view of a patient's condition. This fusion is critical for advancing precision medicine, allowing healthcare providers to tailor interventions based on comprehensive insights.
The adoption of AI and ML also addresses several operational challenges by automating routine tasks, reducing inter-operator variability, and accelerating turnaround times. This makes radiomics more scalable and accessible in busy clinical environments.
As AI continues to evolve, ongoing research focuses on enhancing algorithm transparency, interpretability, and regulatory compliance to build trust among clinicians and patients. Overall, the synergy between AI, ML, and radiomics is a pivotal trend driving innovation and adoption in the healthcare industry, unlocking new possibilities for personalized, data-driven care.
In this report, the Global Radiomics Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:
Company Profiles: Detailed analysis of the major companies presents in the Global Radiomics Market.
Global Radiomics market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report: