Importance of Computer Vision in Medical Technologies
The healthcare industry has already seen many benefits from the rise of artificial intelligence (AI) solutions. One of the emerging AI fields today is computer vision, which can potentially support many different applications delivering life-saving functionalities for patients.
The emerging field of computer vision focuses on training computers to replicate human sight and understand objects in front of it. Currently, the most widespread use cases for computer vision and healthcare are related to radiology and imaging. AI-powered solutions are finding increasing support among doctors because of their help in the diagnosis of diseases and conditions from various scans such as X-ray, and MR, or CT.
Computer vision implications for medical use as follows: (1) precise diagnoses, (2) timely detection of illnesses, (3) heightened medical processes, (4) medical imaging, (5) computer vision for health monitoring and (6) nuclear medicine suggest a host of benefits to the healthcare industry.
- Precise Diagnoses
Computer vision systems offer precise diagnoses, minimizing false positives. The technology can potentially obliterate the requirement for redundant surgical procedures and expensive therapies. Computer vision algorithms trained using a vast amount of training data can detect the slightest presence of a condition that may typically be missed out by human doctors because of their sensory limitations. The use of computer vision in healthcare diagnosis can provide significantly high levels of precision, which may, in the coming days, go up to 100 percent.
- Timely Detection of Illness
The chance of curing fatal diseases, such as cancer, increases considerably when doctors diagnose earlier. Computer vision enables the detection of early symptoms with high certainty owing to its finely tuned pattern-recognition capability. This can be useful in timely treatment and saving countless lives for the long term.
- Heightened Medical Process
Computer vision in healthcare can considerably lessen the time doctors usually take in analyzing reports and images. It frees and offers them more time to spend with patients and provide personalized and constructive advice. Enhancing the quality of physician-patient interactions can also assist medical professionals in giving consultation to more and more patients. Computer vision in healthcare supports caregivers to deliver efficient and accurate healthcare services through its life-saving applications.
- Medical Imaging
For the last decades, computer-supported medical imaging application has been a trustworthy help for physicians. It doesn’t only create and analyze images, but also becomes an assistant and helps doctors interpret. The application is used to read and convert 2D scan images into interactive 3D models that enable medical professionals to gain a detailed understanding of a patient’s health condition.
- Computer Vision for Health Monitoring
By leveraging computer vision technology, doctors can analyze health and fitness metrics to help patients make faster and better medical decisions. Today, it is being utilized by healthcare centers to measure the blood lost during surgeries. This can assist in taking emergency measures if the quantity of blood lost reaches the last stage. Additionally, the technology can also be leveraged to measure people’s body fat percentage using images taken from regular cameras.
- Nuclear Medicine
As a section of clinical medicine, nuclear medicine deals with the use of radionuclide pharmaceuticals in diagnosis. Sometimes computer vision techniques of remote radiation therapy are also referred to as nuclear medicine. In diagnostics, it mainly utilizes single-photon emission computed tomography and positron emission tomography.
As the healthcare industry embraces more innovations and cutting-edge technologies, it will direct its gaze to computer vision. The technology offers assistance in many different medical practice areas, starting from the analysis of medical imaging to providing accurate data about phenomena that are hard to measure. In the future, we will see an increasing number of healthcare institutions experiment with computer vision for better patient experience.