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Artificial intelligence in cardiac radiology

La radiologia medica volume 125, pages 1186–1199 (2020)Cite this article

Abstract

Artificial intelligence (AI) is entering the clinical arena, and in the early stage, its implementation will be focused on the automatization tasks, improving diagnostic accuracy and reducing reading time. Many studies investigate the potential role of AI to support cardiac radiologist in their day-to-day tasks, assisting in segmentation, quantification, and reporting tasks. In addition, AI algorithms can be also utilized to optimize image reconstruction and image quality. Since these algorithms will play an important role in the field of cardiac radiology, it is increasingly important for radiologists to be familiar with the potential applications of AI. The main focus of this article is to provide an overview of cardiac-related AI applications for CT and MRI studies, as well as non-imaging-based applications for reporting and image optimization.

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Affiliations

  1. Division of Cardiothoracic Imaging, Department of Radiology and Imaging Sciences, Emory University Hospital | Emory Healthcare, Inc., 1365 Clifton Road NE, Suite - AT503, Atlanta, GA, 30322, USA

    Marly van Assen, Scott J. Lee & Carlo N. De Cecco

  2. Department of Imaging, Centro Cardiologico Monzino, IRCCS, Milan, Italy

    Giuseppe Muscogiuri

  3. Dipartimento di Scienze Medico Chirurgiche e Medicina Traslazionale, Universita degli Studi Roma La Sapienza, Rome, Italy

    Damiano Caruso & Andrea Laghi

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  1. Marly van Assen
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  2. Giuseppe Muscogiuri
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  3. Damiano Caruso
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  4. Scott J. Lee
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  5. Andrea Laghi
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  6. Carlo N. De Cecco
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Correspondence to Carlo N. De Cecco.

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Dr. De Cecco receives institutional research funding from Siemens Healthineers. Dr. Laghi receives funding or financial compensation from speakers’ bureau, GE Healthcare, Guerbet, Bayer, Merck, and Bracco. All other authors have conflicts of interests.

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van Assen, M., Muscogiuri, G., Caruso, D. et al. Artificial intelligence in cardiac radiology. Radiol med 125, 1186–1199 (2020). https://doi.org/10.1007/s11547-020-01277-w

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  • DOI: https://doi.org/10.1007/s11547-020-01277-w

Keywords

  • Cardiac imaging
  • Artificial intelligence
  • Computed tomography
  • Magnetic resonance imaging