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, and 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: Active contour based diagnosis models.
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 magnetic resonance imaging (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
Active contour-based diagnosis model is a key innovation area in artificial intelligence
A segmentation method known as "active contour" separates the image's important pixels for further processing and analysis by applying energy forces and limitations.
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 300+ companies, spanning technology vendors, established healthcare companies, and up-and-coming start-ups engaged in the development and application of active contour-based diagnosis models.
Key players in active contour-based diagnosis models – 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 active contour based diagnosis models
Source: GlobalData Patent Analytics
Koninklijke Philips is the leading patent filer in the active contour-based diagnosis models. Some other leading patent filers include Siemens and Heartflow.
In terms of application diversity, Applied LifeSciences & Systems leads, followed by Magic Leap and Abbott Laboratories. With regards to geographic reach, Magic Leap leads, followed by Applied LifeSciences & Systems and NuVasive.
One of the techniques most frequently employed in the segmentation of medical images is Active Contour (AC), also known as Deformable Models, which is based on variational models and partial differential equations (PDEs). It separates the important pixels from a picture for further processing and analysis using energy forces and restrictions. Active contours are mostly used in image processing to create closed contours for regions and define smooth shapes in images. It is mostly used to spot asymmetrical shapes in pictures.
To further understand how artificial intelligence is disrupting the healthcare industry, access GlobalData’s latest thematic research report on Artificial Intelligence (AI) in Healthcare.
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