We are in the midst of a technical renaissance, with artificial intelligence (AI) leading the way. Of the many promising tools within AI, computer vision is undoubtedly most distinguished for its ability to generate incredible innovation, especially in the medical field. However, before investigating how computer vision can transform healthcare, we need to clearly understand what AI is and the important subfields that support it.
Central Technology
First, it is important to take a step back and view computer vision from a wider hierarchy of AI. This structure begins with the foundations of AI and rises through machine learning before reaching its peak in computer vision.
The current enthusiasm artificial intelligence The term was cast endlessly in its lack of context. AI at the heart of it is its technology Allows computers to rival human intelligence.
It is generally summarized, but ai and Machine Learning It has a clear meaning. in fact, Machine learning is a branch of AI Rather than relying on pre-programmed responses or other human interventions, it focuses on using vast amounts of data so that machines can acquire knowledge and learn from it. When mimicking neurons in the human brain, machine learning models are constantly trained through neural networks that grant the ability to analyze and extract information.
Computer Vision It is the most specialized area of all the technologies mentioned. Simply put, Computer vision is built on machine learning models to allow computers to process and “display” visual data, such as images and videos. This allows the computer to understand text-based issues as well as solve real problems that require “vision” such as surgery and anti-theft video tracking. After all, computer vision is a practical branch of AI, as photography is worth a thousand words.
Application of computer vision for medical imaging
Currently, computer vision plays an active role in several medical fields, including radiology and pathology. Regarding radiology, Computer vision is used to interpret X-ray, ultrasound, and MRI results. In particular, machines use computer vision to analyze the images these technologies provide for efficiency and accuracy. Similarly, in the field of pathology, computer vision is used in systems to analyze human body tissues to detect a variety of diseases such as cancer. As these machines continue to improve, they are becoming increasingly useful for critical diagnostics that require near perfect accuracy and execution.
Below is an example of how beneficial computer vision can be for human health. Take some time to consider the context of your brain tumor. Many of them grow rapidly and require rapid medical intervention to be removed immediately. Medical professionals can accurately segment and identify tumors using computer vision assistancereducing turnaround time for such serious surgeries. This approach increases both resource and time efficiency compared to purely manual analysis alternatives.
Segmentation and identification of brain tumors using artificial intelligence and computer vision (image courtesy of Nahyan Habib Khan)
The meaning of the future
The future is bright for computer vision with no signs of stopping progress. As more medical data becomes available and statistical noise gradually decreases, AI reaches the point where diagnosis is nearly complete. Additionally, the combination of augmented reality and computer vision allows for more complex healthcare issues to be addressed and resolved. For example, because overcrowding in hospitals is a prominent problem in today's society, online consulting is a promising proposal that can be implemented by integrating computer vision and augmented reality. In non-urgent medical situations, patients can attend online consultations, where doctors communicate with them using future-proofing techniques. To further improve the problem, systems using computer vision while participating in online appointments can provide real-time interpretations to healthcare professionals, making work even easier. Clearing this consideration shows how medical co-pilots with computer vision are currently causing the next great medical revolution.
