The AI in radiology market is projected to grow at a CAGR of 30.45% during the forecast period, reaching a total market size of US$8.59 billion by 2029, up from US$2.27 billion in 2024.
Deep learning algorithms in artificial intelligence (AI) have been perfected in vision-based applications. The medical image analysis domain is expanding rapidly with the realization of variational autoencoders and convolutional neural network techniques. Traditional qualitative assessments for radiographic qualities differ since the measure is easy to perform. Moreover, AI techniques are more advanced at analyzing mechanically difficult information patterns in imaging information. For instance, in radiology, AI algorithms could be designed to measure specific radiographic characteristics, such as the 3D shape of a tumor, every pixel's texture, and pixel intensity within the tumor.
X-ray radiography is when licensed medical doctors study clinical photos and kit a statement or identify and single out diseases that allow disorders to be detected, identified, and monitored. That assessment requires a lot of expertise and experience, which is sometimes susceptible to opinion. In contrast to this qualitative, subjective evaluation, AI is extremely good at identifying subtle patterns in imaging data while automatically providing an objective numerical analysis. Implementing AI to support and assist mammogram physicians can result in more precise and reproducible radiological assessments. This application is opening the door to further development into AI in the radiology market in years or decades to come.
For instance, in February 2023, Avicenna, an AI platform for radiology screening, raised €7 million in a series A venture, bringing its capital base to €10 million. The stage employs image-trained profound learning to recognize and evaluate life-threatening ailments in radiology research facilities. It uses CT scan imaging to prioritize patients with symptoms before diagnosis. Avicenna.AI offers two variations: one for heart attack indications and chance and another for brain damage and stroke chance. The platform assists radiologists in deciding if a patient's life is threatened.
The region's economies are increasingly focusing on creating a sound healthcare system for early patient diagnosis and treatment. In addition, various key companies are focusing on advancing their reach to Asia Pacific countries by building their facilities, leading to the regional market’s growth in the coming years. For instance, in May 2023, Annalise. ai, an AI-based radiology company that is a global leader in the field, established its first Indian center in Chennai.
Through this strategic move, Annalise continues penetrating the world arena with its presence in established and emerging markets like Asia. This translates into a center that specializes in the research and commercialization of new products containing advanced imaging data coupled with computer science that together results in complete AI solutions to support clinical decision-making.
Deep learning algorithms in artificial intelligence (AI) have been perfected in vision-based applications. The medical image analysis domain is expanding rapidly with the realization of variational autoencoders and convolutional neural network techniques. Traditional qualitative assessments for radiographic qualities differ since the measure is easy to perform. Moreover, AI techniques are more advanced at analyzing mechanically difficult information patterns in imaging information. For instance, in radiology, AI algorithms could be designed to measure specific radiographic characteristics, such as the 3D shape of a tumor, every pixel's texture, and pixel intensity within the tumor.
X-ray radiography is when licensed medical doctors study clinical photos and kit a statement or identify and single out diseases that allow disorders to be detected, identified, and monitored. That assessment requires a lot of expertise and experience, which is sometimes susceptible to opinion. In contrast to this qualitative, subjective evaluation, AI is extremely good at identifying subtle patterns in imaging data while automatically providing an objective numerical analysis. Implementing AI to support and assist mammogram physicians can result in more precise and reproducible radiological assessments. This application is opening the door to further development into AI in the radiology market in years or decades to come.
AI IN RADIOLOGY MARKET DRIVERS:
- The increasing requirement from the neurological treatment sector is anticipated to drive AI in the radiology market growth.
For instance, in February 2023, Avicenna, an AI platform for radiology screening, raised €7 million in a series A venture, bringing its capital base to €10 million. The stage employs image-trained profound learning to recognize and evaluate life-threatening ailments in radiology research facilities. It uses CT scan imaging to prioritize patients with symptoms before diagnosis. Avicenna.AI offers two variations: one for heart attack indications and chance and another for brain damage and stroke chance. The platform assists radiologists in deciding if a patient's life is threatened.
AI In Radiology Market Geographical Outlook:
- The Asia Pacific region is expected to hold a substantial AI in radiology market share.
The region's economies are increasingly focusing on creating a sound healthcare system for early patient diagnosis and treatment. In addition, various key companies are focusing on advancing their reach to Asia Pacific countries by building their facilities, leading to the regional market’s growth in the coming years. For instance, in May 2023, Annalise. ai, an AI-based radiology company that is a global leader in the field, established its first Indian center in Chennai.
Through this strategic move, Annalise continues penetrating the world arena with its presence in established and emerging markets like Asia. This translates into a center that specializes in the research and commercialization of new products containing advanced imaging data coupled with computer science that together results in complete AI solutions to support clinical decision-making.
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- Historical data & forecasts from 2022 to 2029
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Market Segmentation:
The AI In Radiology Market is segmented and analyzed as below:- By Technology
- Computer-aided Detection
- Auto-segmentation of Organs
- Natural Language Processing
- Consultation
- Quantification and Kinetics
- Others
- By Application
- Mammography
- Chest Imaging
- Neurology
- Cardiovascular
- Others
- By End-User
- Hospitals
- Diagnostic Imaging Centers
- Others
- By Geography
- North America
- USA
- Canada
- Mexico
- South America
- Brazil
- Argentina
- Others
- Europe
- Germany
- France
- United Kingdom
- Spain
- Others
- Middle East and Africa
- Saudi Arabia
- UAE
- Israel
- Others
- Asia Pacific
- China
- Japan
- India
- South Korea
- Indonesia
- Taiwan
- Others
- North America
Table of Contents
1. INTRODUCTION
2. RESEARCH METHODOLOGY
3. EXECUTIVE SUMMARY
4. MARKET DYNAMICS
5. AI IN RADIOLOGY MARKET BY TECHNOLOGY
6. AI IN RADIOLOGY MARKET BY APPLICATION
7. AI IN RADIOLOGY MARKET BY END-USER
8. AI IN RADIOLOGY MARKET BY GEOGRAPHY
9. COMPETITIVE ENVIRONMENT AND ANALYSIS
10. COMPANY PROFILES
Companies Mentioned
Some of the key companies profiled in this Artificial Intelligence (AI) in Radiology Market report include:- Microsoft Corporation
- Amazon Web Services Inc.
- IBM Corporation
- Rad AI
- Behold.ai
- IMAGEN
- Aidoc
- Koninklijke Philips N.V.
- GE Healthcare
- Siemens Healthcare GmbH
Methodology
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Table Information
Report Attribute | Details |
---|---|
No. of Pages | 145 |
Published | September 2024 |
Forecast Period | 2024 - 2029 |
Estimated Market Value ( USD | $ 2.27 Billion |
Forecasted Market Value ( USD | $ 8.59 Billion |
Compound Annual Growth Rate | 30.4% |
Regions Covered | Global |
No. of Companies Mentioned | 10 |