Computer vision is a domain of artificial intelligence that uses algorithms to understand and interpret digital images. With the development of the field of artificial intelligence, especially in the post-COVID-19 era, computer vision has greatly impacted many industries, including the healthcare industry.
What is Computer Vision?
Computer vision deals with the classification, segmentation, and interpretation of digital images, videos and other visual inputs. Deep learning models enable machines to receive, process, and analyze visual information and overall teach themselves to tell one image from another. Within the field of artificial intelligence, computer vision has long captivated the eyes of researchers.
Computer vision algorithms and hardware have significantly evolved during the past few years, therefore, offering a new arena of opportunities for the healthcare community.
Patient identification systems, medical image analysis, surgical simulation/assistance, disease detection, and rehabilitation software are some of the many computer vision applications in the healthcare industry.
Computer vision can assist medical professionals in accurately diagnosing a disease, for example, medical image analysis allows doctors to view the internal abnormalities in a patient’s body through the techniques of MRI, X-ray radiography, endoscopy, and ultrasound. Pattern recognition and image segmentation are challenging tasks while analyzing medical images, but recent developments in the field of deep learning and artificial intelligence have signaled significant progress in this area.
Another application of computer vision in healthcare is object detection. Even if the area is vast as a football field, object detection easily recognizes people and objects in an image or video. Using a database of known people or objects, object detection technology ensures security and safety, either by identifying a person in a crowd or by identifying a tumor in a body.
Computer vision uses sophisticated algorithms to diagnose different diseases. For example, computer vision uses artificial intelligence to screen skin cancer from skin photographs. Analysis of patients’ images can be used to suggest treatment plans for individual patients.
Computer vision is also helpful in treatment planning as it allows doctors to better understand the effects of various treatment methods by analyzing patients’ images before and after the treatment.
Applications of Computer Vision in Healthcare
Here are a few computer vision use cases in healthcare that have transformed the medical field:
- Improving patient care: Computer vision enables doctors to monitor patients remotely and offer timely care to patients, especially the elderly. Among computer vision applications in healthcare is home-based patient monitoring and rehabilitation, where doctors monitor vitals and track the progress of patients virtually
- Enhancing diagnosis and treatment: Computer-aided diagnosis leverages computer vision to accurately and quickly scan the results of MRI scans, CT scans, and X-rays. Fast and timely detection of abnormalities can offer improved treatment planning and accurate diagnosis.
- Reducing costs: Automating the analysis of medical images through computer vision algorithms reduces the need for manual image interpretation done by radiologists and, in turn, reduces the costs for service providers and patients alike.
The Future of Computer Vision in Healthcare
During the last decade, computer vision technologies have rapidly evolved. Deep learning algorithms have improved the average accuracy of computer vision systems from 50 to 99 percent. From accurate and timely diagnosis to precise surgeries, advancement in artificial intelligence will only add to the promising future that computer vision holds for the healthcare industry.
One significant application of computer vision in healthcare is the timely detection of diseases such as cancer. Computer vision can analyze images of tissue and detect signs of the disease at early stages which would have been otherwise very difficult or impossible for the human eye to detect. The early detection of deadly diseases greatly improves patients’ chances of survival.
Similarly, computer vision technologies have been providing useful assistance to surgeons during operations by providing visual access to patients’ internal organs, which diminishes the risks of making mistakes that can lead to complications. While this technology is still in its early stages, it has already demonstrated to be effective and continues to make improvements.
With the continued advances in artificial intelligence and machine learning, it is safe to say that computer vision will continue to offer more advanced applications for the healthcare sector in the days to come.
Considering the transformative potential that computer vision applications hold for the healthcare industry, we’re excited to witness what future applications of computer vision will be developed and how they’ll improve the quality of healthcare for people around the world.
How AI Superior can help
At AI Superior we enable pharmaceutical companies to build solutions based on computer vision and cutting edge AI. Industry leaders already trust AI Superior’s expertise to develop solutions that enhance diagnosis and treatment such as medical image translation.
Get in touch with us to find out how we can help your business
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