Neural networks have been in use for years to process visual data. Deep learning models can enhance image quality; identify features in image, and spot abnormalities. With these same features, artificial intelligence is transforming the field of radiology while improving patient care in the healthcare industry by saving time and money. When the healthcare industry is driven by AI and machine learning, new exciting solutions can be found for intractable problems in medical imaging.
Healthcare researchers are now intended to use these technologies in face recognition to pursue more important indicator, such as finding those that indicate an onset of breast cancer. The development in visual data application is closely relevant for the number of medical fields, but the introduction of AI combined with ML could change all. The most persuasive reasons for increasing the reliance on AI is that, when the changes are made with the development of an appropriate algorithm, AI is expected to be more reliable than human judgment.
It is evident that most enterprises are looking to solve a wide range of imaging-related issues. Butterfly Network – one of the best-funded companies has worked to apply machine-learning algorithm to help the patients to conduct ultrasound with their own iPhone. The company offers to fit all types of imaging equipment required for ultrasound onto one silicon chip, named as iQ. This developed technology works effectively to create a 3D picture of images by tethering thousands of ultrasonic speakers inside the body.
The benefits of AI in medical imaging will far, gives credibility to the solution and helps in winning the trust of patients. The increased availability of clinical validation will be a major catalyst for its uptake in clinical practice.