Artificial Intelligence (AI) is revolutionizing our daily lives, even though we are yet to fully appreciate its true influence. It is being profoundly integrated into medical science and technology and it is increasingly providing applications and solutions that can be translated into clinical practice.
Medical imaging is one of the most rapidly evolving fields of science and technology thanks to the impactful advances brought about by AI utilization. In CT imaging, for example, despite constant improvements in technique, radiation exposure remains a potential risk for patients. However, AI-based techniques may help overcome this limitation.
Radiation protection and dose optimization supported by AI methods are the topics addressed in the review proposed in this Newsletter, where Prof. Laghi’s team describes the AI-based systems under investigation for CT that may allow dose reductions without affecting image quality.
The two scientific papers included in the “Selected literature” section focus on the potential advantages associated with one of the most promising AI applications – the deep learning-based reconstruction algorithms – able to both reduce radiation dose and optimize image quality in abdominal CT and coronary CT angiography, respectively.
The use of these two CT imaging applications is illustrated in the two clinical cases from the MDCT.net archive reported below, where the injection of contrast material contributes to the technique’s diagnostic accuracy.
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From the MDCT.net team