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Market Research Report
Product code
1092239
AI In Medical Imaging Market - Global Outlook & Forecast 2022-2027 |
AI In Medical Imaging Market - Global Outlook & Forecast 2022-2027 |
Published: June 20, 2022
Arizton Advisory & Intelligence
Content info: 335 Pages
Delivery time: 1-2 business days
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The global AI in medical imaging market is expected to grow at a CAGR of 45.68% during the forecast period 2022-2027.
The constant increase in the number of diagnostic procedures and the decline in the number of radiologists, increasing work pressure on the radiologists, have increased the need for artificial intelligence adoption in the medical imaging space. The researchers are looking for multiple ways to implement artificial intelligence into medical imaging. The demand for artificial intelligence is constantly increasing in the medical imaging software market. From cardiac events, neurological conditions, fractures, or thoracic complications, artificial intelligence helps physicians to diagnose and provide treatment quickly. Implementing AI in medical imaging has enhanced medical screening, improved precision medicine software, reduced physicians' load, etc.
Technological Advancements Revolutionizing AI in Medical Imaging
Vendor's Activity in AI-Based Medical Imaging Market
Siemens Healthineers, General Electric (GE) Company, Koninklijke Philips, and IBM Watson Health are the major players in the global AI in the medical imaging market. International players focus on developing innovative products with advanced technologies and expanding their product portfolio to remain competitive. They are continuously investing extensively in R&D to expand their product portfolio. Manufacturers such as GE Healthcare constantly focus on introducing new products with innovative technology platforms opening the platform (Edison Developer Program) for other companies offering artificial intelligence technologies to scale and deploy their developed applications across GE Healthcare's customer base.
Many major players are engaged in strategic acquisitions and partnerships that continue to be a competitive strategy for the key players, thus helping them grow inorganically. Innovative product approvals coupled with R&D activities are also helping the vendors to expand their presence, enhance growth, and sustain their position in the global market. In 2021, more than 30 countries approved AI in medical imaging technologies that are FDA and CE approved.
There is increasing funding and investments by public and private entities, including large companies, which is also one of the major driving factors of AI in the medical imaging market. For instance, more than 20 start-ups from various regions have received funds to develop AI-based medical imaging technologies.
GEOGRAPHY INSIGHTS
Segmentation by Geography
SEGMENTATION ANALYSIS
Hospitals are purchasing the artificial intelligence medical software suits as a complete package for the usage or taking up one program at a time which is used the most in the industry. The diagnostic imaging center's significant revenue generation is through imaging procedures, and they are primarily involved in implementing advanced products, which will attract customers. For instance, AI in medical imaging, along with clinical data, is helping physicians to predict heart attacks in patients accurately.
Neurology has accounted for the dominating share in the industry. The majority of the initial artificial intelligence product development focuses on downstream processing. This Downstream processing majorly includes artificial intelligence for segmentation, detecting anatomical structures, and quantifying a range of pathologies. Conditions like intracranial hemorrhage, ischemic stroke, primary brain tumors, cerebral metastases, and abnormal white matter signal intensities, which were unmet needs in the industry, has become commercially available solution within the radiology industry.
AI in medical imaging, especially cardiovascular magnetic resonance (CMR), is revolutionized by providing deep learning solutions, especially for image acquisitions, reconstructions, and analysis, which helps in supporting clinical decision-making. CMR is an established tool for routine clinical decision-making, including diagnosis, follow-up, real-time procedures, and pre-procedure planning.
Deep learning methods have enabled more tremendous success in medical image analysis. They have helped high accuracy, efficiency, stability, and scalability. Artificial intelligence tools have become assistive tools in medicine with benefits like error reduction, accuracy, fast computing, and better diagnostics. Natural language processing, Computer Vision, and Context-Aware Computing technologies are also used to create new analysis methods for medical imaging products.
In 2021, Philips showcased its new AI-enabled CT imaging portfolio. Their new CT 5100 with smart workflow application applies artificial intelligence at every step of CT image processing.
Siemens Healthineers's AI-Rad companion chest CT detects and highlights lung nodules. The tumor burden is automatically calculated.
In addition, AI-Rad companion chest X-Ray played a significant role in patient management during the COVID-19 pandemic. The artificial intelligence-Rad companion file automatically processes upright chest X-ray images, pneumothorax, nodule detection, etc. This indicates the consolidations and atelectasis. This indicates the sign of pneumonia caused by the COVID-19 virus.
Artificial intelligence in CT scans and MRI dominated the industry, as much medical imaging using artificial intelligence tools falls into these modality categories. However, artificial intelligence in ultrasound and detecting mammography is largely adopted in the industry.
Segmentation by Technology
Segmentation by Application
Segmentation by Modalities
Segmentation by End-User
Key Vendors
Other Prominent Vendors
KEY QUESTIONS ANSWERED
LIST OF TABLES