Artificial Intelligence in Medical Imaging Market is estimated to be US$ 21.7billion by 2032 with a CAGR of 38.8% over the forecast period (2022-2032)

Published Date: June 2023

Artificial intelligence technology can be used in the healthcare sector in applications such as diagnosis and treatment of complex diseases, it is also being used for machine learning to screen and track patients as well as to predict future infections, using algorithms that process data to identify insightful patterns. This is the main driving force behind AI's ability to detect patterns. Medical imaging can be described as a diagnostic process that involves creating visual aids and representing the image of the human body and observing the performance and function of the human body organs. Artificial intelligence in medical imaging includes two technologies namely deep learning, NLP, in this technology deep learning can be used for the automation of various time-consuming tasks performed by radiologists such as lesion detection, segmentation, classification, monitoring and prediction. A treatment response that is not usually achieved without software. Deep learning technology has emerged as a branch of the machine learning field in the field of human vision, a method of data processing using multiple layers of complex structures or multiple processing layers composed of multiple nonlinear transformations. In recent years, deep learning has made advances in computer vision, speech recognition, natural language processing, audio recognition, and bioinformatics.  Artificial Intelligence Strategies describes ways to integrate and evaluate artificial intelligence strategies to extract patterns from human language, derive meaning, and thus generate feedback, helping the healthcare industry make the best use of unstructured data. Researchers have applied AI to automatically recognize complex patterns in imaging data and provide quantitative assessment of radiographic features in radiation oncology, AI has been applied to different imaging modalities used at different stages of treatment. By using AI in medical imaging, doctors can identify conditions more quickly, encouraging early intervention. Artificially intelligent computer systems are widely used in the medical sciences, with common applications including diagnosing patients, end-to-end drug discovery and development, improving communication between doctors, transcribing medical documents, such as prescriptions, and treating patients remotely. AI helps reduce waiting times for emergency patients who have to be transported from rural and remote areas as it can be used to aid in diagnosis and assessment over long distances AI in teleradiology can be used to facilitate analysis and provide radiologist support. The plan includes extensive government funding and investment to increase the adoption of AI solutions among organizations, which is likely to drive AI in the medical imaging market over the forecast period, and challenge the growth of Artificial Intelligence in Medical Imaging Market during the forecast period.

The report Artificial Intelligence in Medical Imaging Market, By Technology (Deep Learning, NLP), By Modality (Ultrasound Scanners, CT Scanners, MRI System, Optical Coherence Tomography Devices, Other), By Application (Digital Pathology, Oncology, Neurology, Respiratory, & Pulmonary, Cardiology, Oral Diagnostics, Other), By End Use ( Hospital, Clinics, Diagnostic Centers), and By Region (North America, Europe, Asia Pacific, Latin America, and Middle East & Africa) - Trends Analysis and Forecast till 2032 “

Key Highlights:

  • In November 2022, Siemens Healthineers and Atrium Health, a leading nonprofit healthcare provider known for its pediatric, cancer and heart care programs, announced a multi-year value partnership agreement. This strategic agreement will focus care across Atrium Health's service area across the southeastern US, improve health equity and increase economic mobility.
  • In November 2022, Arteries, the developer of the world's first internet platform for medical imaging, now part of Tempus, announced a partnership to organically grow its products and serve radiologists with even more accurate diagnostic tools.
  • In January 2023, GE Healthcare announced that the previously announced spin-off from GE had been completed and that GE Healthcare would begin trading as a separate company on the Nasdaq exchange under the ticker symbol "GEHC" effective at the market opening in January. GE Healthcare will be the first company in the state of Wisconsin to remotely ring the Nasdaq's opening bell, The leadership team will be joined in person at the company's manufacturing facility in Waukesha, Wis., and by employees worldwide.
  • In November 2022, Arteries, the developer of the world's first internet platform for medical imaging, has been awarded a national group procurement contract with Premier Inc. for artificial intelligence solutions for the healthcare category. Effective October 2022, the new agreement allows Premier members, at their discretion, to take advantage of special pricing and terms pre-negotiated by Premier for Artery's medical imaging platform and clinical AI workflow solutions.
  • In November 2022, Caption Health, a leader in using AI and services to improve cardiac ultrasound diagnostics, launched a new Mock AI technology platform for clinical marketing in Australia and clinical and treatment farm bust administrator access to Health Canada.
  • In October 2022, Royal Philips, a global leader in health technology, announced two new advances in MR-only workflows for radiology imaging and stimulation of head and neck cancer. The company's artificial intelligence enabled MRCAT head and neck radiotherapy application, which allows the use of MR as the sole or primary imaging modality for radiotherapy planning among treatment of soft tissue tumors of the head and neck, containing the brain, pelvis, and prostate, has received FDA approval and is commercially available among the US.

Analyst View:

AI-based technologies provide specialists with many tools that help them treat patients effectively. However, AI is a new phase in the medical imaging market and thus, there may be some hurdles to overcome before AI becomes mainstream in medical imaging. Medical imaging can be described as a diagnostic process that involves creating visual aids and representing the image of the human body and observing the performance and function of the human body organs. AI techniques are also the most efficient in identifying the diagnosis of various diseases, the presence of computerized logic as a method for improved medical services offers an unprecedented opportunity to improve patient and clinical group outcomes, reduce costs. AI allows healthcare professionals to better understand their patients' patterns and needs through deep data analysis, as the technology continues to evolve and medical applications are discovered, doctors and nurses will be able to provide better guidance, support and feedback. Innovation in the Artificial Intelligence in Medical Imaging Market is increasing worldwide, driven by technological developments in Artificial Intelligence in Medical Imaging Market products that are more efficient to use.

 Browse 60 market data tables* and 35 figures* through 140 slides and in-depth TOC on “Artificial Intelligence in Medical Imaging Market, By Technology (Deep Learning, NLP), By Modality (Ultrasound Scanners, CT Scanners, MRI System, Optical Coherence Tomography Devices, Other), By Application (Digital Pathology, Oncology, Neurology, Respiratory, & Pulmonary, Cardiology, Oral Diagnostics, Other), By End Use ( Hospital, Clinics, Diagnostic Centers), and By Region (North America, Europe, Asia Pacific, Latin America, and Middle East & Africa) - Trends, Analysis and Forecast till 2032”

Key Market Insights from the report:

Artificial Intelligence in Medical Imaging Market accounted for US$ 1.7 billion in 2022 and is estimated to be US$ 21.7 billion by 2032 and is anticipated to register a CAGR of 38.8%. The Artificial Intelligence in Medical Imaging Market is segmented based on Technology, Modality, Application, End Use and Region.

  • Based on Technology, Artificial Intelligence in Medical Imaging Market is segmented into Food & Beverages, Oilfield, Paper & Pulp, Detergents, Coatings, and Others.
  • Based on Modality, Artificial Intelligence in Medical Imaging Market is segmented into Thickening Agent, Stabilizer, Binder, Anti-Repository Agent, Lubricator, Emulsifier and Excipient.
  • Based on Application, Artificial Intelligence in Medical Imaging Market is segmented into Food & Beverages, Oilfield, Paper & Pulp, Detergents, Coatings, and Others.
  • Based on End use, Artificial Intelligence in Medical Imaging Market is segmented into Thickening Agent, Stabilizer, Binder, Anti-Repository Agent, Lubricator, Emulsifier and Excipient.
  • By Region, the Artificial Intelligence in Medical Imaging Market is segmented into North America, Europe, Asia Pacific, Latin America, and Middle East & Africa.

Competitive Landscape & their strategies of Artificial Intelligence in Medical Imaging Market:

The prominent players operating in the Artificial Intelligence in Medical Imaging Market includes, Siemens Healthcare AG, Arterys, AZmed, Caption Health, Zebra Medical Vision, Inc., Koninklije Philips N.V., Agfa Healthcare, GE Healthcare, Inc., IBM Corporation, and Microsoft Corporation. The market provides detailed information regarding the industrial base, productivity, strengths, manufacturers, and recent trends which will help companies enlarge the businesses and promote financial growth. Furthermore, the report exhibits dynamic factors including segments, sub-segments, regional marketplaces, competition, dominant key players, and market forecasts. In addition, the market includes recent collaborations, mergers, acquisitions, and partnerships along with regulatory frameworks across different regions impacting the market trajectory. Recent technological advances and innovations influencing the global market are included in the report.

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Some Important Points Answered in this Market Report Are Given Below:

  • Explains an overview of the product portfolio, including product development, planning, and positioning
  • Explains details about key operational strategies with a focus on R&D strategies, corporate structure, localization strategies, production capabilities, and financial performance of various companies.
  • Detailed analysis of the market revenue over the forecasted period.
  • Examining various outlooks of the market with the help of Porter’s five forces analysis, PEST & SWOT Analysis.
  • Study on the segments that are anticipated to dominate the market.
  • Study on the regional analysis that is expected to register the highest growth over the forecast period

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