This paper is in the following e-collection/theme issue:

Machine Learning (1370) Imaging Informatics (181) Artificial Intelligence (1186) Decision Support for Health Professionals (1127) Computer-Aided Diagnosis (94) Methods and Instruments in Medical Informatics (101) Tools, Programs and Algorithms (236) Clinical Informatics (904)

Published on in Vol 9, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/30066, first published .
Deep Learning Techniques for Fatty Liver Using Multi-View Ultrasound Images Scanned by Different Scanners: Development and Validation Study

Deep Learning Techniques for Fatty Liver Using Multi-View Ultrasound Images Scanned by Different Scanners: Development and Validation Study

Deep Learning Techniques for Fatty Liver Using Multi-View Ultrasound Images Scanned by Different Scanners: Development and Validation Study

Authors of this article:

Taewoo Kim1 Author Orcid Image ;   Dong Hyun Lee2 Author Orcid Image ;   Eun-Kee Park3 Author Orcid Image ;   Sanghun Choi1 Author Orcid Image
Article Authors Cited by (8) Tweetations (2) Metrics

Taewoo Kim   1 * , BS ;   Dong Hyun Lee   2 * , MD, PhD ;   Eun-Kee Park   3 , PhD ;   Sanghun Choi   1 , PhD

1 School of Mechanical Engineering, Kyungpook National University, Daegu, Republic of Korea

2 Division of Gastroenterology, Department of Internal Medicine, Good Gang-An Hospital, Busan, Republic of Korea

3 Department of Medical Humanities and Social Medicine, College of Medicine, Kosin University, Busan, Republic of Korea

*these authors contributed equally

Corresponding Author:

  • Sanghun Choi, PhD
  • School of Mechanical Engineering
  • Kyungpook National University
  • 80 Daehak-ro
  • Buk-gu
  • Daegu, 41566
  • Republic of Korea
  • Phone: 82 53-950-5578
  • Fax: 82 53-950-6550
  • Email: s-choi@knu.ac.kr