Literature DB >> 32079904

Machine Learning and Deep Neural Networks: Applications in Patient and Scan Preparation, Contrast Medium, and Radiation Dose Optimization.

Matthias Eberhard1, 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.

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Year:  2020        PMID: 32079904     DOI: 10.1097/RTI.0000000000000482

Source DB:  PubMed          Journal:  J Thorac Imaging        ISSN: 0883-5993            Impact factor:   3.000


  5 in total

Review 1.  Overview of Noninterpretive Artificial Intelligence Models for Safety, Quality, Workflow, and Education Applications in Radiology Practice.

Authors:  Yasasvi Tadavarthi; Valeria Makeeva; William Wagstaff; Henry Zhan; Anna Podlasek; Neil Bhatia; Marta Heilbrun; Elizabeth Krupinski; Nabile Safdar; Imon Banerjee; Judy Gichoya; Hari Trivedi
Journal:  Radiol Artif Intell       Date:  2022-02-02

2.  Deep learning for automatic quantification of lung abnormalities in COVID-19 patients: First experience and correlation with clinical parameters.

Authors:  Victor Mergen; Adrian Kobe; Christian Blüthgen; André Euler; Thomas Flohr; Thomas Frauenfelder; Hatem Alkadhi; Matthias Eberhard
Journal:  Eur J Radiol Open       Date:  2020-10-06

Review 3.  From Early Morphometrics to Machine Learning-What Future for Cardiovascular Imaging of the Pulmonary Circulation?

Authors:  Deepa Gopalan; J Simon R Gibbs
Journal:  Diagnostics (Basel)       Date:  2020-11-25

4.  Influence of Percutaneous Drainage Surgery and the Interval to Perform Laparoscopic Cholecystectomy on Acute Cholecystitis through Genetic Algorithm-Based Contrast-Enhanced Ultrasound Imaging.

Authors:  Qiaoying Li; Rong Cheng; Xiao Gao; Limin Zhu
Journal:  Comput Intell Neurosci       Date:  2022-07-30

5.  Machine learning-based prediction of insufficient contrast enhancement in coronary computed tomography angiography.

Authors:  H A Marquering; R N Planken; R R Lopes; T P W van den Boogert; N H J Lobe; T A Verwest; J P S Henriques
Journal:  Eur Radiol       Date:  2022-06-16       Impact factor: 7.034

  5 in total

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