The healthcare industry continues to be a hotbed of innovation. Activity is 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. Buy the report here.
According to GlobalData’s Technology Foresights, which uses over 443,000 patents to analyse innovation intensity for the healthcare industry, there are 200+ innovation areas that will shape the future of the 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. It broadly splits companies into either ‘niche’ or ‘diversified’ innovators.
‘Geographic reach’ refers to the number of different countries each relevant patent is registered in. It 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
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.