The AI In Medical Imaging Global Market Report 2024 by The Business Research Company provides market overview across 60+ geographies in the seven regions – Asia-Pacific, Western Europe, Eastern Europe, North America, South America, the Middle East, and Africa, encompassing 27 major global industries. The report presents a comprehensive analysis over a ten-year historic period (2010-2021) and extends its insights into a ten-year forecast period (2023-2033).
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According to The Business Research Company’s AI In Medical Imaging Global Market Report 2024, The ai in medical imaging market size has grown exponentially in recent years. It will grow from $2.07 billion in 2023 to $2.85 billion in 2024 at a compound annual growth rate (CAGR) of 37.6%. The growth in the historic period can be attributed to increased volume of medical imaging data, increased demand for improved diagnostic accuracy, growing burden of chronic diseases, enhanced workflow efficiency, increased healthcare expenditure..
The ai in medical imaging market size is expected to see exponential growth in the next few years. It will grow to $10.34 billion in 2028 at a compound annual growth rate (CAGR) of 37.9%. The growth in the forecast period can be attributed to integration with electronic health records (ehr), growing application in image-guided interventions, emergence of ai-powered personalized medicine, increased focus on preventive healthcare, global expansion of telemedicine.. Major trends in the forecast period include enhanced imaging modalities with ai, interoperability and data sharing, regulatory framework development, increased industry collaboration, growing emphasis on explainable ai..
The growing adoption of AI in radiology is expected to propel the AI in medical imaging market going forward. Radiology refers to the medical specialty that focuses on the diagnosis and treatment of diseases and injuries using medical imaging techniques. AI in medical imaging is widely used in radiology to enhance the interpretation of medical images and improve the efficiency and accuracy of radiological workflows, such as automated image analysis, computer-aided detection, and image reconstruction and enhancement. For instance, in February 2023, Inside Precision Medicine, a US-based media brand, published an article that said AI adoption in radiology increased to 30% in 2020 compared to previous years. Furthermore, in November 2022, according to Itransition, a US-based software development company, 30 percent of radiologists used AI in their clinical practices in 2022, although 20 percent of practices plan to buy AI tools in the coming years. Therefore, the growing adoption of AI in radiology will drive the AI in medical imaging market.
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The ai in medical imaging market covered in this report is segmented –
1) By Technology: Deep Learning, Natural Language Processing (NLP), Other Technologies
2) By Solution: Software Tools, Services
3) By Modality: Computed Tomography (CT) Scan, Magnetic Resonance Imaging (MRI), X-Rays, Ultrasound, Nuclear Imaging
4) By Application: Digital Pathology, Oncology, Cardiovascular, Neurology, Lung (Respiratory System), Breast (Mammography), Liver (GI), Oral Diagnostics, Other Applications
5) By End-Use: Hospitals, Diagnostic Imaging Centers, Other End-Users
Technological advancements are the key trends gaining popularity in the AI in medical imaging market. Major companies in the AI in the medical imaging market are developing innovative technologies to sustain their position in the AI in the medical imaging market. For instance, in November 2022, Viz.AI Inc., a US-based medical imaging company, launched its AI-powered radiology suite. This innovative technology integrates into the picture archiving and communication systems (PACS) of healthcare organizations to securely facilitate access to imaging data across departments and streamline patient diagnosis. Additionally, it includes specific features such as AI-powered alerts that notify radiologists of suspected diseases in real-time, prioritized worklists that help radiologists focus on the most urgent cases, real-time communication tools that allow radiologists to collaborate with other care team members, and benefits by improving patient outcomes, reducing costs, and increasing efficiency.
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