Dublin, July 06, 2022 (GLOBE NEWSWIRE) — The “AI in the Medical Imaging Market – Global Outlook & Forecast 2022-2027” report has been added to ResearchAndMarkets.com’s offer.
The demand for artificial intelligence is constantly increasing in the medical imaging software market. From cardiac events, neurological disorders, fractures or thoracic complications, artificial intelligence helps doctors quickly diagnose and administer treatment. The implementation of AI in medical imaging has improved medical screening, improved precision medicine software, reduced the burden on doctors, etc.
Technological advances that are revolutionizing AI in medical imaging
Many technological advancements have been made in AI-based medical imaging technologies, which have shown their increasing adoption in high-income countries. Some of the improvements include the development of integrated rtiI software, which can be directly integrated into imaging equipment (MRI or CT scanner) that facilitates the automation of medical image analysis. Other developments include the integration of smartphone technology into AI in medical imaging, where primary care professionals can screen non-invasively for a variety of conditions using a smartphone.
AI in medical imaging has attracted the attention of several radiologists worldwide. It provides faster and more accurate results and reduces diagnostic errors at a lower cost compared to traditional medical imaging methods. Therefore, radiologists believe that AI in medical imaging could offer a huge opportunity for its increasing implementation in the coming years.
Hospitals buy the artificial intelligence medical software packs as a complete package for use or incorporate one program at a time which is most widely used in the industry. The diagnostic imaging center’s significant revenues are generated by imaging procedures, and they are mainly involved in the implementation of advanced products, which will attract customers.
For example, AI in medical imaging, along with clinical data, helps doctors accurately predict heart attacks in patients.
Neurology is responsible for the dominant share in the industry. Most of the initial artificial intelligence product development is focused on downstream processing. This downstream processing mainly involves artificial intelligence for segmentation, detecting anatomical structures and quantifying a range of pathologies.
Conditions such as intracranial hemorrhage, ischemic stroke, primary brain tumors, cerebral metastases and abnormal white matter signal intensities, which were not met in the industry, have become a commercially available solution within the radiology industry.
AI in medical imaging, especially cardiovascular magnetic resonance (CMR), has revolutionized by providing deep learning solutions, especially for image acquisitions, reconstructions and analysis, helping to support clinical decision-making. CMR is a proven tool for routine clinical decision-making, including diagnosis, follow-up, real-time procedures, and pre-procedure planning.
Deep learning methods have enabled more massive success in medical image analysis. They have contributed to high accuracy, efficiency, stability and scalability. Artificial intelligence tools have become tools in medicine with benefits such as error reduction, accuracy, fast computing and better diagnostics. Natural Language Processing, Computer Vision and Context-Aware Computing technologies are also being used to create new analytical methods for medical imaging products.
Segmentation by technology
Segmentation by Application
Respiratory and Pulmonary
Segmentation by modalities
Segmentation by end user
Main topics covered:
1 Research methodology
2 research objectives
3 Research process
4 Scope and coverage
4.1 Market definition
4.2 Base year
4.3 Scope of the study
5 Report assumptions and warnings
6 Market at a glance
7.2 Artificial intelligence in the healthcare sector
7.3 Artificial intelligence in medical imaging
8 market opportunities and trends
8.1 Technological advances in AI-based medical imaging
8.2 Increasing adoption of AI-based medical imaging in developed countries
8.3 Increasing tendency of radiologists towards AI-based medical imaging
9 Factors Enabling Market Growth
9.1 Increase in number of diagnostic procedures
9.2 Expanding investment opportunities in AI-based medical imaging
9.3 Increase of approved/commercial AI-based medical imaging platforms
9.4 Advances in AI, cloud-based and hybrid image processing solutions
10 market restrictions
10.1 Less adoption of AI-based medical imaging in Lmics
10.2 Lack of integration and practical applications of AI in medical imaging
10.3 Concerns over data breaches in AI-based medical imaging
11 Market landscape
11.1 Market overview
11.2 Market size and forecast
11.3 Five Forces Analysis
12.1 Market snapshot and growth engine
12.2 Market overview
12.3 Deep learning
13.1 Market snapshot and growth engine
13.2 Market overview
13.4 Respiratory and Pulmonary
13.6 Breast cancer
14.1 Market snapshot and growth engine
14.2 Market overview
14.7 Nuclear Imaging
15 End user
15.1 Market snapshot and growth engine
15.2 Market overview
15.4 Diagnostic Imaging Centers
16.1 Market snapshot and growth engine
16.2 Geographical overview
17 North America
20. Latin America
21. Middle East and Africa
22. Competitive Landscape
22.1 Match overview
22.2 Market Share Analysis
23. Main Company Profiles
23.1 General Electric
23.2 Siemens Healthineers
23.3 Royal Philips
23.4 IBM Watson Health
24. Other Prominent Sellers
25. Report overview
25.1 Main takeaways
25.2 Strategic Recommendations
26. Quantitative Summary
For more information about this report, visit https://www.researchandmarkets.com/r/a34jm5
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