Machine Learning and Deep Neural Networks
Matthias Eberhard, Hatem Alkadhi
Abstract
Artificial intelligence (AI) algorithms are dependent on a high amount of robust data and the application of appropriate computational power and software. AI offers the potential for major changes in cardiothoracic imaging. Beyond image processing, machine learning and deep learning have the potential to support the image acquisition process. AI applications may improve patient care through superior image quality and have the potential to lower radiation dose with AI-driven reconstruction algorithms and may help avoid overscanning. This review summarizes recent promising applications of AI in patient and scan preparation as well as contrast medium and radiation dose optimization.
Topics & Concepts
MedicineArtificial intelligenceDeep learningArtificial neural networkMachine learningImage processingImage qualityApplications of artificial intelligenceProcess (computing)SoftwareComputer scienceImage (mathematics)Programming languageOperating systemAdvanced X-ray and CT ImagingRadiation Dose and ImagingMedical Imaging Techniques and Applications