Titlebook: Artificial Intelligence in Cardiothoracic Imaging; Carlo N. De Cecco,Marly van Assen,Tim Leiner Book 2022 The Editor(s) (if applicable) an

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Patient Selection and Scan Preparation Optimization: The Role of Artificial Intelligence been developed so far with the aim to support patient selection and scan preparation. However, there are several possibilities where AI may improve clinical decision support systems for image ordering, patient scheduling, protocoling, and patient positioning due to its capability to analyze complex

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Artificial Intelligence-Based Image Reconstruction in Cardiac Magnetic Resonance reconstruction to disease diagnosis and treatment. Particularly, in recent years, there has been a significant growth in the use of AI and ML algorithms, especially deep learning (DL)-based methods, for medical image reconstruction. DL techniques have shown to be competitive and often superior over

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Artificial Intelligence-Based Contrast Medium OptimizationIn many hospitals around the world, CM is still used in a “one-size-fits-all” fashion, usually with a “safety margin” regarding CM volume, guaranteeing sufficient enhancement even in the heavier patient. The primary reason for using standard protocols instead of optimising CM for individual patients

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https://doi.org/10.1007/978-3-540-73776-6 attention is paid to these steps and a multidisciplinary team of healthcare professionals, data scientists, and AI engineers is employed in the process of AI development and validation, promising results can be observed that could improve treatment and have a major impact on both patient and healthcare professional.

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