The market is expected to increase at CAGR of 25.76% during the forecast period 2022-2032
BIS Research, the global leader in providing market intelligence on deep technologies, has released its latest study titled AI-Enabled Medical Imaging Solutions Market – A Global and Regional Analysis.
According to this study, the global AI-enabled imaging solutions market was valued at $1.85 billion in 2022 and is projected to reach $18.35 billion by 2032.
The following factors are responsible for the increase in demand for ai-enabled medical imaging solutions:
- Increasing awareness regarding early detection of chronic disorders
- Facilitation of better clinical decision-making and increased accuracy with artificial intelligence
- Increasing therapeutic applications of ai-enabled devices
- Technologically advancements in ai-enabled products and the increasing regulatory approvals for them
The detailed study is a compilation of 33 market data tables and 195 figures spread through 294 pages.
Check out the detailed table of content here:
Analyst’s Take on the Market Projection
According to Stayendrsingh Rajput, Lead Analyst, BIS Research, “Artificial intelligence is fundamentally transforming the medical imaging industry, both in terms of diagnostic accuracy and productivity. Novel cognitive algorithms promise to offer several concrete prospects, such as quantitative imaging, prognostic risk assessment, unceasing treatment monitoring, and above all, utmost diagnostic accuracy. The market is anticipated to grow during the forecast period owing to increasing awareness regarding the early detection of chronic disorders, facilitation of better clinical decision-making, and increased accuracy with artificial intelligence.”
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Major Existing Industry Leaders in the AI-Enabled Medical Imaging Solutions Market
The companies that are profiled have been selected based on input gathered from primary experts and analyzing company coverage, product portfolio, and market penetration. Some of the established names in the market are:
- Agfa-Gevaert Group
- Blackford Analysis Limited
- Butterfly Network, Inc.
- Canon Inc.
- Caption Health
- Carestream Health Inc.
- FUJIFILM Holdings Corporation
- General Electric Company
- Hologic, Inc.
- iCAD, Inc.
- Koninklijke Philips N.V.
- NVIDIA Corporation
- Siemens Healthineers AG
- VUNO, Inc.
Recent Developments in the Global AI-Enabled Medical Imaging Solutions Market
- In November 2022, Aidoc received U.S. FDA approval for its CT-based AI solution for the diagnosis of aortic dissection (AD) and all vessel occlusions (VOs).
- In September 2022, Aidoc partnered with Sana Klinikum Lichtenberg, which is the largest German private hospital network of 55 facilities. Through this partnership, Aidoc’s AI solution for pulmonary embolism (PE) will be integrated into all the facilities of Sana Klinikum Lichtenberg.
- In June 2022, Blackford Analysis Limited partnered with Us2.ai to bring advanced echocardiography analysis tools to the Blackford Platform.
- In May 2022, Butterfly Network, Inc. partnered with the Medical University of South Carolina to work on transforming patient care, health education, and medical research.
- In August 2021, Blackford Analysis Limited partnered with Qlarity Imaging to bring QuantX Diagnostic AI to Radiologists via the Blackford Platform.
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About BIS Research:
BIS Research is a global B2B market intelligence and advisory firm focusing on deep technology and related emerging trends which can disrupt the market dynamics in the near future. We publish more than 200 market intelligence studies annually that focus on several deep technology verticals.
Our strategic market analysis emphasizes on market estimations, technology analysis, emerging high-growth applications, deeply segmented granular country-level market data, and other important market parameters useful in the strategic decision-making for senior management.
BIS Research offers syndicate as well as custom studies and expert consultations to firms, providing them with specific and actionable insights on novel technology markets, business models, and competitive landscapes.
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