AI in Medical Imaging Market Size to Garner USD 14,271.80 Million by 2032| Precedence Research
Press Releases
Nov 30, 2023
OTAWA,ON, Nov. 30, 2023 /PRNewswire/ — The global AI in medical imaging market size is estimated to garner USD 14,271.80 million by 2032, Increasing from USD 762.84 million in 2022.
The global AI in medical imaging market is expected to expand at the double digit CAGR of 33.1% during the forecast period 2023 to 2032. One of the most promising areas of health and medical innovation is the use of artificial intelligence (AI) in medical imaging.
AI in Medical Imaging Market Statistics by Regions 2022 to 2032
- The North America AI in medical imaging market size accounted for USD 379.11 million in 2022 and is projected to reach around USD 5,680.48 million by 2032, expanding at a healthy CAGR of 33.60% from 2023 to 2032.
- The Europe AI in medical imaging market size accounted for USD 284.14 million in 2022 and is anticipated to reach around USD 3,989 million by 2032, expanding at a healthy CAGR of 32.60% from 2023 to 2032.
- The Asia Pacific AI in medical imaging market size accounted for USD 219.64 million in 2022 and is anticipated to reach around USD 3,407.61 million by 2032, progressing a healthy CAGR of 34.20% from 2023 to 2032.
- The LAMEA AI in medical imaging market size accounted for USD 99.27 million in 2022 and is anticipated to reach around USD 1,194.71 million by 2032, progressing a healthy CAGR of 30.10% from 2023 to 2032.
Forecasted AI in Medical Imaging Market Size and Y-O-Y (2022-2032)
Forecast Years |
Market Size ($ Million) |
Y-O-Y % |
2022 |
762.84 |
26.60 % |
2023 |
982.16 |
28.75 % |
2024 |
1,275.86 |
29.90 % |
2025 |
1,674.56 |
31.25 % |
2026 |
2,212.64 |
32.13 % |
2027 |
2,964.12 |
33.96 % |
2028 |
3,984.56 |
34.43 % |
2029 |
5,448.17 |
36.73 % |
2030 |
7,508.26 |
37.81 % |
2031 |
10,350.89 |
37.86 % |
2032 |
14,271.80 |
37.88 % |
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Global AI in Medical Imaging Market Revenue Share (%), by Regions 2022-2032
By Region |
2022 |
2023 |
2024 |
2025 |
2026 |
2027 |
2028 |
2029 |
2030 |
2031 |
2032 |
North America |
38.46 % |
38.60 % |
38.74 % |
38.88 % |
39.02 % |
39.16 % |
39.30 % |
39.44 % |
39.58 % |
39.67 % |
39.80 % |
Europe |
29.04 % |
28.93 % |
28.82 % |
28.71 % |
28.60 % |
28.49 % |
28.38 % |
28.27 % |
28.16 % |
28.06 % |
27.95 % |
Asia Pacific |
22.18 % |
22.36 % |
22.55 % |
22.73 % |
22.91 % |
23.09 % |
23.28 % |
23.46 % |
23.64 % |
23.72 % |
23.88 % |
LAMEA |
10.32 % |
10.11 % |
9.90 % |
9.68 % |
9.47 % |
9.26 % |
9.04 % |
8.83 % |
8.62 % |
8.55 % |
8.37 % |
Total |
100.00 % |
100.00 % |
100.00 % |
100.00 % |
100.00 % |
100.00 % |
100.00 % |
100.00 % |
100.00 % |
100.00 % |
100.00 % |
By Application |
2022 |
2023 |
2024 |
2025 |
2026 |
2027 |
2028 |
2029 |
2030 |
2031 |
2032 |
CAGR |
Digital Pathology |
96.04 |
123.27 |
159.64 |
208.88 |
275.14 |
367.44 |
492.39 |
671.15 |
922.01 |
1,267.82 |
1,742.79 |
32.70 % |
Oncology |
85.29 |
110.15 |
143.53 |
188.97 |
250.47 |
336.58 |
453.84 |
622.45 |
860.45 |
1,190.82 |
1,647.24 |
33.50 % |
Cardiovascular |
82.69 |
106.22 |
137.67 |
180.27 |
237.64 |
317.61 |
425.95 |
581.05 |
798.88 |
1,097.48 |
1,509.20 |
32.80 % |
Neurology |
158.98 |
205.79 |
268.76 |
354.63 |
471.07 |
634.4 |
857.28 |
1,178.30 |
1,632.30 |
2,255.51 |
3,123.75 |
33.80 % |
Lungs (Respiratory System) |
64.23 |
83.12 |
108.51 |
143.13 |
190.07 |
255.88 |
345.66 |
474.94 |
657.72 |
910.64 |
1,261.49 |
33.70 % |
Breast (Mammography) |
139.37 |
180.94 |
236.99 |
313.6 |
417.75 |
564.15 |
764.44 |
1,053.54 |
1,463.36 |
2,023.08 |
2,807.74 |
34.20 % |
Liver (GI) |
54.85 |
70.36 |
91.06 |
119.08 |
156.77 |
209.23 |
280.21 |
381.71 |
524.08 |
716.63 |
983.28 |
32.60 % |
Oral Diagnostics |
31.73 |
40.44 |
51.99 |
67.53 |
88.28 |
117.01 |
155.6 |
210.44 |
286.82 |
393.76 |
537.79 |
31.70 % |
Others |
49.66 |
61.88 |
77.7 |
98.46 |
125.46 |
161.84 |
209.19 |
274.59 |
362.65 |
495.15 |
658.53 |
28.20 % |
Global AI in Medical Imaging Market Revenue, by Application 2022-2032 (US$ Million)
AI-driven medical imaging has transformed the field of medicine by enabling doctors to provide accurate, effective, and customized diagnosis and treatment regimens. Medical imaging technology has reached previously unheard-of levels of speed and accuracy due to advanced deep-learning algorithms, allowing medical practitioners to identify abnormalities and diagnose diseases with accuracy. This progress has led to substantial developments in diagnostic accuracy, treatment efficiency, and overall patient care quality.
AI in medical imaging is increasing the precision of medical diagnosis, screening results, and the capacity to predict disease. AI-powered medical imaging uses powerful processing power and complex algorithms to quickly identify issues, which speeds up diagnosis and action. These technologies provide doctors with quick decision help while analyzing CT scans or X-rays, reducing the time required for image interpretation. AI and machine learning technologies in medical imaging prove crucial for monitoring subtle changes, especially in conditions like brain tumors and cancers where precise treatment methods are important. Incorporating AI enhances precision medicine, enabling differentiation between various types of diseases and predicting survival rates based on accurate measurements of grade and stage.
AI technology reduces medical professionals’ workload by eliminating manual labour, automating the analysis, and minimizing stress. Examining hundreds of diagnostic images, pathologists performing conventional cancer screening faced a huge increase in effort and diagnostic time. The process is simplified by AI-enabled medical imaging technologies, which also address the global scarcity of medical personnel by offering decision help. AI in medical imaging improves patient outcomes through faster diagnosis, more individualized therapies, and accurate medical interventions, particularly in critical care situations such as strokes, when AI techniques speed diagnosis and save time.
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The AI in Medical Imaging Market is segmented based on technology, solution, modality, application, end use and region. Factors such as the increasing demand for early disease detection, shortage of healthcare professionals, and growing adoption of AI in healthcare are driving the growth of the market. However, data privacy and security concerns, lack of transparency and explainability, regulatory approval and standardization, clinical validation and acceptance, and high costs are limiting the growth of the market.
Regional Snapshot
Global AI in Medical Imaging Market Revenue, by Regions 2022-2032 (US$ Million)
By Region |
2022 |
2023 |
2024 |
2025 |
2026 |
2027 |
2028 |
2029 |
2030 |
2031 |
2032 |
CAGR |
North America |
293.39 |
379.11 |
494.27 |
651.07 |
863.37 |
1,160.75 |
1,565.93 |
2,148.76 |
2,971.77 |
4,106.57 |
5,680.48 |
33.60 % |
Europe |
221.53 |
284.14 |
367.7 |
480.77 |
632.82 |
844.48 |
1,130.82 |
1,540.20 |
2,114.33 |
2,904.27 |
3,989.00 |
32.60 % |
Asia Pacific |
169.2 |
219.64 |
287.64 |
380.59 |
506.92 |
684.49 |
927.41 |
1,278.00 |
1,774.95 |
2,455.18 |
3,407.61 |
34.20 % |
LAMEA |
78.73 |
99.27 |
126.25 |
162.14 |
209.54 |
274.4 |
360.4 |
481.21 |
647.21 |
884.86 |
1,194.71 |
30.10 % |
North America dominated the market in 2022, holding a major share and is expected to grow rapidly due to the rising adoption of AI in Medical Imaging and technological advancements in the market. For instance, In the U.S., Medic Vision and Gateway Diagnostic Imaging have completed an innovative research project aimed at improving MRI efficiency using artificial intelligence (AI) in medical imaging. Gateway Diagnostic Imaging, a leading provider with 11 facilities throughout North Texas, requires increasing efficiency and productivity in the face of rising MRI scan demand.
Gateway adopted new brief scanning protocols in conjunction with Medic Vision’s iQMR, an AI-assisted iterative image reconstruction software system, resulting in images of equal or higher quality to original protocols. This strategic shift, integrated with an updated scheduling system, increased MRI productivity by 22%, allowing for an average of 4 more patients per day per scanner. Thus, this project’s success reflects the growing importance and positive impact of AI adoption.
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AI Technology Insights:
The deep learning segment is expected to grow faster during the forecast period. Deep learning has grown into an adverse impact in medical imaging with unparalleled potential to improve the accuracy of diagnoses, optimize processes, and personalize therapies. Its ability to analyze large datasets of medical images, such as X-rays, CT scans, and MRIs, allows it to detect minute abnormalities and patterns that human radiologists can overlook. In cancer diagnosis, deep learning algorithms outperform traditional methods, detecting cancer cells in tissue samples with greater accuracy, leading to earlier diagnoses and improved treatment outcomes. Similarly, in neurological conditions, these algorithms excel in detecting subtle changes in brain scans, assisting in the early diagnosis of diseases like as Alzheimer’s and Parkinson’s.
Solution Insights:
The software tools/ platforms segment of the AI in medical imaging market is the fastest-growing segment, driven by increasing demand for AI-powered solutions, advancements in AI technology, and the growing availability of AI-specific software tools. These software tools and platforms are making AI-powered solutions more accessible and affordable to healthcare providers, which is accelerating the adoption of AI in medical imaging. This leads to improved diagnostic accuracy, streamlined workflows, and personalized treatment plans for patients.
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Market Dynamics
Driver: Advancement of AI for Enhanced Clinical Efficiency
The introduction of artificial intelligence (AI) into medical imaging is being influenced by a critical need for increased clinical efficacy and efficiency. The rapid expansion of radiological imaging data, surpassing the availability of adequately trained readers, has created a major disparity. Additionally, a decrease in imaging payments has prompted healthcare providers to improve productivity, resulting in an enormous rise in radiologists’ workloads. As a result of these constraints, where radiologists have to analyze an image every 3-4 seconds throughout an 8-hour workday, errors become a necessary consequence of this limited environment.
The effortless integration of AI components into the imaging workflow is being strategically pushed to overcome these issues and maximize the productivity of medical imaging. This integration aims to reduce the workload on radiologists by providing pre-screened images and identified features, reducing manual input, and minimizing the potential for errors. Advances in technology connected to artificial intelligence (AI) in medical imaging are being developed by proactive initiatives and policies. The focus includes beyond mere lesion detection, focusing on the consistent selection of clinically meaningful endpoints such as survival, symptoms, and the imperative need for treatment. Thus, the use of AI in medical imaging represents a significant change in the direction of better clinical results while addressing the challenges presented by increasing workloads and changing payment models.
Restraint: High cost and regulatory compliance
The use of artificial intelligence in medical imaging involves high initial costs associated with technology procurement, infrastructure upgrades, and personnel education. Demonstrating the long-term economic benefits and clinical impact is essential to overcome resistance based on cost considerations. Moreover, the regulatory framework for artificial intelligence in healthcare is changing, and maintaining compliance with several regulatory frameworks is a major issue. It is crucial for universal acceptability to achieve consistency in AI algorithms, validation methods, and ethical principles across diverse areas and healthcare systems.
Opportunity:
The increasing implementation of AI imaging solutions in surgical workflows presents transformative opportunities within the medical imaging market. The National Health System (NHS) in the United Kingdom and a partner firm have collaborated to generate 3D reconstructions using AI algorithms, starting with pre-operative planning, and utilizing traditional CT or MRI images. Surgeons utilize these reconstructions to assess a patient’s anatomy, enhancing their strategic planning. Artificial intelligence (AI) tools, such as OrthoGrid’s surgical navigation, use powerful computers to evaluate images in real-time during surgery. This helps surgeons by giving them immediate feedback, lowering errors, and improving patient outcomes.
Theator’s Surgical Intelligence Platform uses artificial intelligence (AI) to evaluate surgical footage captured after surgery, providing insightful information on procedural difficulties and areas for improvement. Post-surgery, Theator’s Surgical Intelligence Platform utilizes AI to analyze recorded surgical videos, generating valuable insights into procedural challenges and opportunities for improvement. These advancements underscore the pivotal role of AI in reshaping surgical practices and fostering a new era of precision and consistency in medical imaging applications.
Browse More Insights:
Medical Imaging Displays Market: The global medical imaging displays market size was valued at USD 5.24 billion in 2022 and it is expected to hit around USD 9.14 billion by 2032, expanding at a CAGR of 5.72% from 2023 to 2032.
Medical Imaging Reagents Market: The global medical imaging reagents market size was exhibited at USD 16 billion in 2022 and is expected to hit around USD 30.17 billion by 2032, poised to grow at a projected CAGR of 6.6% from 2023 to 2032.
Medical Imaging Outsourcing Market: The global medical imaging outsourcing market size was valued at USD 8.26 Billion in 2022 and is expected to reach USD 11.92 Billion by 2032, with a compound annual growth rate (CAGR) of 4% during the forecast period 2023 to 2032.
Artificial Intelligence (AI) in Biopharmaceutical Market: The global artificial intelligence (AI) in biopharmaceutical market size was estimated at USD 0.86 billion in 2022 and is projected to hit around USD 14.07 billion by 2032, registering a CAGR of 32.3% during the forecast period from 2023 to 2032.
Radiopharmaceuticals Market: The global radiopharmaceuticals market size surpassed USD 5.2 billion in 2022 and is projected to hit around USD 13.67 billion by 2032, registering a CAGR of 10.2% during the forecast period 2023 to 2032.
Generative AI in Biology Market: The global generative AI in biology market size was estimated at USD 74 million in 2022 and it is projected to reach around USD 363.37 million by 2032, growing at a CAGR of 17.3% during the forecast period 2023 to 2032.
Point-of-Care Medical Imaging Market: The global point-of-care medical imaging market size was exhibited at USD 3.72 billion in 2022 and it is expected to hit around USD 5.9 billion by 2032, growing at a CAGR of 4.72% during the forecast period from 2023 to 2032.
Generative AI in Medicine Market: The global generative AI in medicine market size was valued at USD 501.06 million in 2022 and it is expected to hit around USD 21,586.75 million by 2032, expanding at a CAGR of 45.69% over the forecast period from 2023 to 2032.
Healthcare Information Systems Market: The global healthcare information systems market was estimated at USD 296 billion in 2022 and is expected to hit around US$ 641.98 billion by 2032, poised to grow at a CAGR of 8.10% from 2023 to 2032.
Healthcare Informatics Market: The global healthcare informatics market size is expected to be worth around US$ 104.80 billion by 2032 from at US$ 33 billion in 2022, expanding growth at a CAGR of 12.30% from 2023 to 2032.
Recent Developments
- In May 2023, Royal Philips, a major player in health technology, announced the Philips CT 3500, an innovative CT system aimed to meet the needs of regular radiography and high-volume screening campaigns. Using powerful AI technology, this system combines a number of features aimed at image reconstruction and process optimization. These aspects help to ensure consistent, quick, and high-quality imaging, allowing physicians to make confident diagnosis and maximize return on investment. The Philips CT 3500 is designed specifically for demanding, high-volume care scenarios.
- In April 2023, Medical artificial intelligence (AI) solution company Vuno received a US patent for its AI-based medical image analysis technology. This patent pertains to a technology aimed at simplifying the process of correcting lesion areas identified by medical personnel while examining medical images such as X-rays, magnetic resonance imaging scans, and computerized tomography (CT) scans in clinical environments.
- In June 2023, GE HealthCare announced officially received FDA clearance and introduced Sonic DL, an advanced deep learning technology engineered to significantly speed up the image acquisition process in magnetic resonance imaging (MRI).
- In Oct 2022, Google Cloud announced Medical Imaging Suite, a new technology it says can help with accessibility and interoperability of radiology and other imaging data.
Market Key Players:
- Agfa-Gevaert Group/Agfa HealthCare
- Arterys
- AI
- AZmed
- Butterfly Network
- Caption Health
- CellmatiQ
- dentalXrai
- Digital Diagnostics
- EchoNous
- GLEAMER
- HeartVista
- iCAD
- Lunit
- Mediaire
- MEDO
- Nanox Imaging
- Paige AI
- Perimeter Medical Imaging AI
- Predible Health
- 1QB Information Technology
- Qure.ai
- Quantib
- QLARITY IMAGING
- Quibim
- Renalytix
- Therapixel
- Ultromics
- Viz.ai
- VUNO
Key Market Segments
By AI Technology
- Deep Learning
- Natural Language Processing (NLP)
- Others
By Solution
- Software Tools/ Platform
- Services
- Integration
- Deployment
By Modality
- CT Scan
- MRI
- X-rays
- Ultrasound Imaging
- Nuclear Imaging
By Application
- Digital Pathology
- Oncology
- Cardiovascular
- Neurology
- Lung (Respiratory System)
- Breast (Mammography)
- Liver (GI)
- Oral Diagnostics
- Other
By End Use
- Hospitals and Clinics
- Research Laboratories and Diagnostic Centers
- Others (Ambulatory Surgical Centres, Intensive care at home, etc.)
By Geography
- North America
- Europe
- Asia-Pacific
- Latin America
- Middle East & Africa (MEA)
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