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Computer Vision Applications in Medicine
Since it enables computers to recognize objects, computer vision plays a key role in the ongoing automation of the medical field. Let’s take a look at some examples.
Precise Detection of Diseases
Computer vision can be used to detect diseases by analyzing visual symptoms; for example, the detection of various suspicious pigmented lesions (SPLs) on the skin can help a computer diagnose melanoma, a type of skin cancer. Identifying each lesion and coming up with a diagnosis manually is very time-consuming. However, there is an easier method, one that uses a computer vision system to detect melanoma. To understand what melanoma-related SPLs look like, a predefined dataset of images with and without melanoma-related SPLs was given to the system so that it could learn to distinguish the two categories. According to MIT News, researchers “trained the system using 20,388 wide-field images from 133 patients at the Hospital Gregorio Marañón in Madrid, as well as publicly available images.” Using this trained system, a device such as a phone could then be used to classify SPLs on the skin and diagnose melanoma. This system has “achieved more than 90.3 percent sensitivity in distinguishing SPLs [suspicious pigmented lesions] from non-suspicious lesions, skin, and complex backgrounds’’.
Given that melanoma is responsible for over 70% of skin cancer deaths, such a computer vision application could have a useful and potentially life-saving role in healthcare. By combining computer vision with deep neural networks, devices could detect common signs of harmful diseases quickly and accurately. If this concept was extended to diagnosing other diseases, it could have a profound effect on the healthcare industry.
Humans performing surgery without medical robots will soon become a thing of the past. Today, many medical robots can perform many medical procedures with great precision. According to Addepto, “[t]he 3D, high-definition imaging that medical robots use, increases the vision of the operation field and makes depth perception accessible. As a result, surgical operations are more accurate and take less time.”
One such company that applies computer vision in the healthcare field is RSIP Vision. Their systems could “provide the surgeon with a highly accurate and effective real-time in-op view of the surgery environment.” By using solutions that enable correct and helpful navigation in surgery, surgeons can give patients better treatment when surgery is needed.
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