The healthcare industry continues to be a hotbed of innovation, with activity driven by telemedicine, real-time diagnostics, smart hospitals and access to digital therapies, as well as the growing importance of technologies such as artificial intelligence (AI), the Internet of Things (IoT), augmented reality (AR), robotics and data management practices. In the last three years alone, there have been over 106,000 patents filed and granted in the healthcare industry, according to GlobalData’s report on Artificial Intelligence in Healthcare: AI-assisted motion artefact reduction.
However, not all innovations are equal and nor do they follow a constant upward trend. Instead, their evolution takes the form of an S-shaped curve that reflects their typical lifecycle from early emergence to accelerating adoption, before finally stabilising and reaching maturity.
Identifying where a particular innovation is on this journey, especially those that are in the emerging and accelerating stages, is essential for understanding their current level of adoption and the likely future trajectory and impact they will have.
200+ innovations will shape the healthcare industry
According to GlobalData’s Technology Foresights, which plots the S-curve for the healthcare industry using innovation intensity models built on over 443,000 patents, there are 200+ innovation areas that will shape the future of the industry.
Within the emerging innovation stage, drug delivery device security, microscopic image analysis models, and cellular imaging techniques are disruptive technologies that are in the early stages of application and should be tracked closely. Smart balloon catheters, automated immunoassay analysers, and AI-assisted MRI are some of the accelerating innovation areas, where adoption has been steadily increasing. Among maturing innovation areas are smart fitness training system and non-invasive physiological monitoring, which are now well established in the industry.
Innovation S-curve for artificial intelligence in the healthcare industry
AI-assisted motion artefact reduction is a key innovation area in artificial intelligence
Medical imaging is generally accompanied by subject- or hardware-related acquisition artefacts, which make accurate diagnosis difficult. Various methods such as view randomisation, view averaging, repetition time matching to the respiratory cycle, hybrid imaging, ROPE and COPE help in reducing motion artefacts.
GlobalData’s analysis also uncovers the companies at the forefront of each innovation area and assesses the potential reach and impact of their patenting activity across different applications and geographies. According to GlobalData, there are 80+ companies, spanning technology vendors, established healthcare companies, and up-and-coming start-ups engaged in the development and application of AI-assisted motion artefact reduction.
Key players in AI-assisted motion artefact reduction – a disruptive innovation in the healthcare industry
‘Application diversity’ measures the number of different applications identified for each relevant patent and broadly splits companies into either ‘niche’ or ‘diversified’ innovators.
‘Geographic reach’ refers to the number of different countries each relevant patent is registered in and reflects the breadth of geographic application intended, ranging from ‘global’ to ‘local’.
Patent volumes related to AI-assisted motion artefact reduction
Source: GlobalData Patent Analytics
Heartflow is the leading patent filer in the AI-assisted motion artefact reduction market. Some other leading patent filers include Koninklijke Philips and Siemens.
In terms of application diversity, People.ai leads the pack, followed by Lifetrack Medical Systems and Bayer. With regards to geographic reach, Nikon leads, followed by Stryker and Medtronic.
Various revolutionary deep learning-based approaches to remove motion artefacts are being introduced. The convolutional neural networks showed good results in artefact reduction after being trained with synthetic image pairings. Comparing the restored photos against artefact-contaminated images enhanced the medical diagnostics.
To further understand how artificial intelligence is disrupting the healthcare industry, access GlobalData’s latest thematic research report on Artificial Intelligence (AI) in Healthcare.
Subscribe to our Newsletter
Get industry leading news, data and analysis delivered to your inbox
GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.
GlobalData’s Patent Analytics tracks patent filings and grants from official offices around the world. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
