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Computer vision allows a physician to take full advantage of medical imaging data for better diagnosis and treatment of diseases.
FREMONT, CA: Computer vision implies training computers to replicate human sight and figuring out the objects in front of it. It permits extensive use of medical imaging data. This technology has invaded all the medical fields, where it executes the job of a physician in a matter of seconds. Computer vision is developed by combining AI and deep learning that uses algorithms to process images to make a faster and more accurate diagnosis. Computer vision, when used in diagnosis, can help cut costs in care delivery as the time-consuming and tedious tasks are carried out by machines, allowing clinicians to provide better patient care and boosting patient outcomes.
It was, earlier, a challenge to use computer vision due to the complexity of dealing with medical images. With the advent of deep learning and neural networks, detection, segmentation, and classification of images are made possible. In computer vision, low-level processing involves basic imaging operations like noise filtering, image sharpening, and contrast enhancement, while mid-level processing includes image segmentation and pattern recognition. The high-level processing and analysis using computer vision are carried out by employing methods that utilize 3D image segmentation, 3D visualization and animation, and other medical diagnosis methods, including neural networks.
The medical applications in computer vision help physicians perform early identification of significant diseases in the brain, kidney, prostate, and many other organs. Thus, the computer vision has shown a great application in surgery and therapy of diseases. Recently, tools have been developed to measure blood loss during childbirth and predict heart rhythm disorders. When the amount of blood loss is accurately measured, then the physician can treat the women appropriately in a way to prevent blood loss. Notably, it assists in diagnosing diseases like hemorrhages and strokes, which are incredibly time-sensitive. Recently, researches are conducted towards detecting pulmonary nodules in lung scans and diagnose nodules from the high-resolution CT scans. Additionally, it is the medical imaging that has a significant impact on computer vision as it uses enormous computing power while increasing its use in medical imaging.
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