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

Machine Learning (1465) Imaging Informatics (193) Artificial Intelligence (1371) Decision Support for Health Professionals (1185) Computer-Aided Diagnosis (128) Methods and Instruments in Medical Informatics (126) Tools, Programs and Algorithms (266) Clinical Informatics (1022)

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 (11) Tweetations (2) Metrics

Journals

  1. Micucci M, Iula A. Recent Advances in Machine Learning Applied to Ultrasound Imaging. Electronics 2022;11(11):1800 View
  2. Kim T, Kim W, Lee C, Chae K, Bak S, Kwon S, Jin G, Park E, Choi S. Quantitative computed tomography imaging-based classification of cement dust-exposed subjects with an artificial neural network technique. Computers in Biology and Medicine 2022;141:105162 View
  3. Yang Y, Liu J, Sun C, Shi Y, Hsing J, Kamya A, Keller C, Antil N, Rubin D, Wang H, Ying H, Zhao X, Wu Y, Nguyen M, Lu Y, Yang F, Huang P, Hsing A, Wu J, Zhu S. Nonalcoholic fatty liver disease (NAFLD) detection and deep learning in a Chinese community-based population. European Radiology 2023;33(8):5894 View
  4. Harrison A, Li B, Hsu T, Chen C, Yu W, Tai J, Lu L, Tai D. Steatosis Quantification on Ultrasound Images by a Deep Learning Algorithm on Patients Undergoing Weight Changes. Diagnostics 2023;13(20):3225 View
  5. Singh S, Hoque S, Zekry A, Sowmya A. Radiological Diagnosis of Chronic Liver Disease and Hepatocellular Carcinoma: A Review. Journal of Medical Systems 2023;47(1) View
  6. Zamanian H, Shalbaf A, Zali M, Khalaj A, Dehghan P, Tabesh M, Hatami B, Alizadehsani R, Tan R, Acharya U. Application of artificial intelligence techniques for non-alcoholic fatty liver disease diagnosis: A systematic review (2005–2023). Computer Methods and Programs in Biomedicine 2024;244:107932 View
  7. Fu Y, Zang D, Lin B, He Q, Xie Y, Zhang B, Liu Y, Jin Y, He Y, Guan T. A Deep Learning Method Enables Quantitative and Automatic Measurement of Rat Liver Histology in NAFLD. International Journal of Imaging Systems and Technology 2024;34(4) View
  8. Kaffas A, Bhatraju K, Vo-Phamhi J, Tiyarattanachai T, Antil N, Negrete L, Kamaya A, Shen L. Development of a Deep Learning Model for Classification of Hepatic Steatosis from Clinical Standard Ultrasound. Ultrasound in Medicine & Biology 2024 View