AI in Medical Imaging Market

AI in Medical Imaging Market: Focus on Medical Image Processing, 2020-2030

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AI in Medical Imaging Market Overview

The AI in medical imaging market is estimated to be worth $589 million in 2020 and is expected to grow at CAGR of 31% during the forecast period. Deep learning is a machine learning approach that involves the use of intuitive algorithms and artificial neural networks to facilitate unsupervised pattern recognition / insight generation from large volumes of unstructured data. This technology is gradually being incorporated in a variety of applications across the healthcare sector, including imaging-based medical diagnosis and data processing. Specifically concerning medical imaging, deep learning has the potential to be used to automate information processing and result interpretation for a variety of diagnostic images, such as X-rays, computed tomography scans, magnetic resonance imaging, and positron emission tomography. In this context, it is worth mentioning that the manual examination of medical images is limited, both in terms of accuracy (resulting in misdiagnosis) and throughput (leading to delays in communication of results). As a result, in situations characterized by low physician / pathologist to patient ratios, the conventional mode of operation is rendered inadequate. Experts have predicted a shortage of 10,000 to 40,000 physicians, by 2030, in the US alone.

Further, it is estimated that 90% of medical data generated in hospitals is in the form of images; this puts an immense burden on radiologists and other consulting physicians related to processing such large volumes of data. In fact, according to a study published in the American Journal of Medicine, ~15% of reported medical cases in developed countries, are misdiagnosed. In addition, close to 1.5 million individuals are estimated to die each year, across the world, due to misdiagnosis. On the other hand, accurate artificial intelligence diagnosis at an early stage has been demonstrated to allow significant cost savings for both patients and healthcare providers. In this scenario, deep learning and other artificial intelligence imaging technologies are currently being developed / investigated to automate such processes.

Over time, various industry stakeholders have designed proprietary deep learning algorithms for processing of medical images. Presently, many innovators claim to have developed the means to train computers to read and triage medical images, and recognize patterns related to both temporal and spatial changes (which are not even visible to the naked eye). Experts in the field of artificial intelligence diagnosis also believe that the use of deep learning can actually speed up the processing and interpretation of radiology data by 20%, reducing the rate of false positives by approximately 10%. It is also worth mentioning that in the past few years, the FDA has provided the necessary clearances and approved the use for a variety of deep learning or AI imaging software. Moreover, several technology-focused innovators, such as (in alphabetical order) IBM, GE Healthcare and Google, have entered into strategic alliances with big pharma players, in order to bring proprietary deep learning-based medical solutions to the market. This upcoming segment of the pharmaceutical industry that exists at the interface between medicine and information technology, has garnered the attention of prominent venture capital firms and strategic investors. In the long term, the AI in medical imaging market is anticipated witness significant market growth as more machine learning based solutions are approved for use, during the forecast period. 

The context of deep learning market report, published by Roots Analysis List of deep learning-based medical image processing solutions from the research report of Roots Analysis This image presents the company valuation analysis in deep learning market

Key Companies in AI in Medical Imaging Market

Examples of key companies engaged in AI in medical imaging market (which have also been profiled in this market report; the complete list of companies is available in the full report) include Artelus, Arterys, Butterfly Network, ContextVision, Enlitic, Echonous, GE Healthcare, InferVision and VUNO. This market report includes an easily searchable excel database of all the companies using deep learning in medical image analysis, worldwide.

Scope of the Report

The ‘AI in Medical Imaging Market: Focus on Medical Image Processing, 2020-2030’ market report features an extensive study on the current market landscape, market size, market share, market growth, market forecast, market outlook and future opportunities of the AI based medical imaging market. The market research report presents an in-depth analysis, highlighting the capabilities of various stakeholders engaged in AI based medical imaging market.

This image highlights the cost saving analysis in deep learning market This image provides information on investments received by the companies engaged in deep learning market This image highlights the partnership activity undertaken by players engaged in deep learning market

In addition to other elements, the market research report provides:

  • A detailed review of the current market landscape of deep learning solutions for medical image processing, along with information on their status of development (launched / under development), regulatory approvals (FDA, CE mark, others), type of offering (diagnostic software / tool, diagnostic software / tool + device), type of image processed (X-ray, MRI, CT, ultrasound), application area (lung infections / respiratory disorders, brain injuries / disorders, lung cancer, cardiac conditions / cardiovascular disorders, bone deformities / orthopedic disorders, breast cancer and others). In addition, it presents details of companies developing such solutions, such as their year of establishment, company size, location of headquarters and focus area (in terms of type of deployment model). Further, it highlights key features of each solution and affiliated technologies. 
  • An in-depth analysis of the contemporary market trends, presented using three schematic representations, including [A] a grid representation illustrating the distribution of solutions based on application area, type of image processed and type of offering and [B] an insightful map representation highlighting the geographical activity of the players. 
  • Elaborate profiles of key players that are engaged in the development of deep learning-based solutions intended for processing of medical images. Each company profile features a brief overview of the company (including information on year of establishment, number of employees, location of headquarters and key members of the executive team), details of their respective portfolio of solutions, recent developments and an informed future outlook.
  • An analysis of the partnerships that have been inked by stakeholders in AI in medical imaging market, during the time period 2016-2020 (till June), covering research / development agreements, solution utilization agreements, solution integration agreements, marketing / distribution agreements, other relevant types of deals.
  • An analysis of the investments made, including seed financing, venture capital financing, debt financing, grants and others, in companies that are focused on developing deep learning-based solutions intended for processing of medical images.
  • An elaborate valuation analysis of companies that are involved in applying deep learning in solutions intended for processing of medical images. Further, we have built a multi-variable dependent valuation model to estimate the current valuation of a number of companies engaged in AI in medical imaging market.
  • A clinical trial analysis of completed, ongoing and planned studies (available on ct.gov), focused on the assessment deep learning-based software solutions, based on various parameters, such as trial registration year, trial recruitment status, trial design, target therapeutic area, leading industry and non-industry players, and geographical locations of trials. 
  • An in-depth analysis of over 3,000 patents related to deep learning and medical images that have been filed / granted till June 2020, highlighting key trends associated with these patents, across type of patent, publication year and application year, regional applicability, CPC symbols, emerging focus areas, leading patent assignees (in terms of number of patents filed / granted), patent benchmarking and valuation.  
  • An insightful analysis highlighting cost saving potential associated with the use of deep learning solutions intended for processing of medical images, based on information gathered from close to 30 countries, taking into consideration various parameters, such as total number of radiologists, annual salary of radiologists, number of scans performed (across each type of image) and increase in efficiency by adoption of deep learning solutions. 
  • An insightful discussion on the views presented by various industry and non-industry experts present across the globe, on various portals, such as YouTube and other media platforms. The summary of insights provided by each expert is discussed across focus area, current industry status / challenges and future outlook. 

The key objective of AI in medical imaging market report is to provide a detailed market analysis in order to estimate the existing market size, market trends, market value, statistics and future opportunity for AI based medical imaging market during the forecast period (medical image processing segment), such as global radiology spending across countries, number of radiologists employed across different regions of globe, annual salary of radiologists, rate of adoption of deep learning-based solutions, we have developed informed estimates on the financial evolution of the market, over the forecast period 2020-2030. The market report also provides details on the likely distribution of the current and forecasted opportunity across [A] application area (lung infections / respiratory disorders, brain injuries / disorders, lung cancer, cardiac conditions / cardiovascular disorders, bone deformities / orthopedic disorders, breast cancer and others), [B] type of image processed (X-ray, MRI, CT, ultrasound) and [C] region (North America, Europe and Asia Pacific / Rest of the World). In order to account for future uncertainties and to add robustness to our market forecast model, we have provided three scenarios, namely conservative, base and optimistic scenarios, representing different tracks of the industry’s growth. 

This image provides information on patents that have been filed / granted related to deep learning solutions This image presents clinical assessment landscape of deep learning market The current and future market trends of deep learning market according to Roots Analysis

The opinions and insights presented in the market report were also influenced by discussions held with multiple stakeholders in AI in medical imaging market. The market research report features detailed transcripts of interviews held with the following individuals (in alphabetical order):

  • Walter de Back (Research Scientist, Context Vision, Q2 2020)
  • Dr. Vikas Karade (CEO, AlgoSurg, Q2 2020)
  • Babak Rasolzadeh (Senior Director of Product, Arterys, Q2 2020)
  • Carla Leibowitz, (Head of Strategy and Marketing, Arterys, Q2 2017)
  • Mausumi Acharya, (CEO, Advenio Technosys, Q2 2017)
  • Deekshith Marla, (CTO, Arya.ai) and Sanjay Bhadra, (COO, Arya.ai, Q2 2017)

All actual figures have been sourced and analyzed from publicly available information forums. Financial figures mentioned in this market research report are in USD, unless otherwise specified.

Frequently Asked Questions

Question 1: What is AI in medical imaging?

Answer: AI in medical imaging refers to the use of artificial intelligence and deep learning algorithms to be used to automate information processing and result interpretation for a variety of diagnostic images, such as X-rays, computed tomography scans, magnetic resonance imaging, and positron emission tomography.

Question 2: How big is the AI in medical imaging market?

Answer: The AI in medical imaging industry size is estimated to be worth $589 million in 2020.

Question 3: What is the projected market growth of the AI in medical imaging market?

Answer: The AI in medical imaging market is expected to grow at compounded annual growth rate (CAGR) of 31% during the forecast period 2020 – 2030.

Question 4: Who are the leading companies in the AI in medical imaging market?

Answer: Examples of key companies providing AI in medical imaging services include Artelus, Arterys, Butterfly Network, ContextVision, Enlitic, Echonous, GE Healthcare, InferVision and VUNO. Each of these companies have detail company profiles in our market report; the complete list of companies is available in the full report.

Question 5: How many software solutions are presently available developed by the players engaged in AI in medical imaging industry?

Answer: Over 200 software solutions are presently available developed by the players engaged in AI in medical imaging industry.

Question 6: How much money has been invested by stakeholders engaged in the AI in medical imaging market?

Answer: More than USD 2 billion has been invested by stakeholders engaged in the AI in medical imaging industry on developing deep learning-based software solutions.

Question 7: Which type of diagnostic image is primarily processed by the software solutions developed by players engaged in AI in medical imaging market?

Answer: Presently, close to 30% of the players engaged in AI in medical imaging market offer software solutions for processing X-ray images.

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