PUBLISHER: Grand View Research | PRODUCT CODE: 1376081
PUBLISHER: Grand View Research | PRODUCT CODE: 1376081
The global computer vision in healthcare market size is expected to reach USD 15.60 billion by 2030, according to a new report by Grand View Research, Inc.. The market is anticipated to grow at a CAGR of 35.2% from 2023 to 2030. Computer vision in healthcare is a subset of artificial intelligence dedicated to techniques like visual object detection, classification, tracking, depth estimation in images, and semantic segmentation, among others. The primary aim of computer vision (CV) is to emulate the human brain's capacity to receive and interpret visual information. Leveraging algorithms for image processing, computer vision enables more prompt and precise diagnostics compared to traditional physician-based approaches.
By offloading complex tasks and time-consuming processes to machines, computer systems in healthcare contribute to streamlining workflows, empowering physicians to redirect their attention toward providing enhanced patient care as the technology handles intricate diagnostic processes efficiently. The proliferation of AI-based technologies in healthcare is a key driver for the expansion of the healthcare computer vision market. AI empowers machines to execute tasks typically performed by humans. Within computer vision, AI technologies encompass natural language processing (NLP), allowing computers to comprehend text and spoken language like human understanding.
For instance, in July 2022, according to the ACR Data Science Institute, a U.S.-based entity dedicated to formulating frameworks for integrating machine learning (ML) in radiological professions, approximately 30% of radiologists have embraced AI in their clinical practices. This integration enhances the radiology imaging process, exemplifying how adopting AI-based technologies fuels the growth of healthcare computer vision market. Leveraging computer vision technology enables doctors to analyze health and fitness metrics, facilitating quicker and more informed patient medical decisions.
At present, healthcare centers are integrating this technology to measure blood loss during surgeries, particularly in procedures, such as C-sections. This real-time measurement can be instrumental in triggering emergency interventions when blood loss reaches critical levels. Furthermore, computer vision technology extends its utility to gauging body fat percentages by using images captured through standard cameras. This application showcases the technology's versatility, as it goes beyond surgical contexts to offer non-invasive assessments of health-related parameters.