AI in medical imaging can be described as a diagnostic procedure that involves the creation of visual aids and pictorial representations of the human body and involves the monitoring of the performance and function of the organs of the human body. With the integration of artificial intelligence (AI) into healthcare and medical imaging, the way diagnostics and the entire procedure is performed is changing. The AI ​​supports the surgeons in carrying out the image acquisition process and diagnosing these images for inference and personalized treatment in relation to each individual and patient. Artificial intelligence consists mainly of robots and machine learning. Machine learning involves the recognition and application of algorithms in computer systems to render images. In contrast, robots support patients, doctors and operators in visualization and diagnostic procedures.

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Increasing demand for the influx of large and complex datasets, government initiatives to encourage the use of AI-based technologies, increasing attention to reducing radiologists’ workloads, artificial intelligence (AI) tools in the medical industry, increased funding for the AI based start-ups by private players and an increase in cross-industry collaborations and partnerships are some of the factors driving this market.

Diseases are becoming more common, which has increased the number of diagnostic procedures performed, which has increased market demand. In addition, AI-driven medical imaging provides patients with earlier detection, better diagnosis, and personalized care. AI-based medical imaging systems have seen numerous technological improvements and are becoming increasingly popular in high-income countries. Creating integrated rtiI software that can be easily integrated into imaging equipment (such as MRI or CT scanners) is one of the…