Literature DB >> 34256218

Understanding artificial intelligence based radiology studies: CNN architecture.

Simukayi Mutasa1, Shawn Sun2, Richard Ha3.   

Abstract

Artificial intelligence (AI) in radiology has gained wide interest due to the development of neural network architectures with high performance in computer vision related tasks. As AI based software programs become more integrated into the clinical workflow, radiologists can benefit from better understanding the principles of artificial intelligence. This series aims to explain basic concepts of AI and its applications in medical imaging. In this article, we will review the background of neural network architecture and its application in imaging analysis.
Copyright © 2021 Elsevier Inc. All rights reserved.

Keywords:  Artificial intelligence; CNN architecture; Deep learning

Year:  2021        PMID: 34256218     DOI: 10.1016/j.clinimag.2021.06.033

Source DB:  PubMed          Journal:  Clin Imaging        ISSN: 0899-7071            Impact factor:   1.605


  1 in total

1.  Implementation of a Convolutional Neural Network for Eye Blink Artifacts Removal From the Electroencephalography Signal.

Authors:  Marcin Jurczak; Marcin Kołodziej; Andrzej Majkowski
Journal:  Front Neurosci       Date:  2022-02-11       Impact factor: 4.677

  1 in total

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