How to use Computer vision in Healthcare?
Computer vision is an emerging technology that is being used in medical fields for many applications. Some of the applications include imaging, point of care diagnostic testing and diagnosing diseases, surgical interruption, surgical navigation and analysis of MRI images. The technology has been used to automate many healthcare procedures like Triage and Augmented Reality surgery. It’s not just for image recognition anymore; it is also capable of detecting patterns, uncovering insights and reducing costs in this sector. It is used in healthcare to achieve automation, efficiency, and accuracy.
Two specific areas where computer vision is instrumental in healthcare are Disease Diagnosis and Surgical Intention. Diseases can be diagnosed through the use of algorithms that match symptoms to diseases with high specificity. Computer Vision then assists the surgeon by highlighting blood vessels that need to be cut or cauterized.
Below are some examples of how computer vision is being used in the healthcare industry.
- Computer vision training has been shown to help diagnose Parkinson’s disease with 95% accuracy.
- Computer vision systems are also used in cancer diagnosis and prognosis, where they can be more accurate than a human doctor because it cannot be influenced by human biases or emotions.
- Pioneering research has been done using computer vision to identify eye diseases like diabetic retinopathy and glaucoma, which can lead to blindness if not treated in time.
- The medical field is currently facing a shortage of oncologists and radiologists that use computed tomography (CT) scans for diagnosing cancerous tumors, so the use of AI for these tasks will undoubtedly help alleviate this shortage.