Application of Deep Learning in Quantitative Analysis of 2-Dimensional Ultrasound Imaging of Nonalcoholic Fatty Liver Disease.

Journal: Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine

Published Date: Jan 1, 2020

Abstract

OBJECTIVES: To verify the value of deep learning in diagnosing nonalcoholic fatty liver disease (NAFLD) by comparing 3 image-processing techniques.

Authors

Wen Cao
Xing An

Beijing Research Institute, Shenzhen Mindray Biomedical Electronics Co, Ltd, Beijing, China.
Longfei Cong

Beijing Research Institute, Shenzhen Mindray Biomedical Electronics Co, Ltd, Beijing, China.
Chaoyang Lyu

Department of Ultrasound Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
Qian Zhou

Department of Computer Science, City University of Hong Kong, Hong Kong, Hong Kong SAR, China.
Ruijun Guo

Department of Ultrasound Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.

Keywords

Deep Learning Evaluation Studies as Topic Image Interpretation, Computer-Assisted Liver Non-alcoholic Fatty Liver Disease Sensitivity and Specificity Severity of Illness Index Ultrasonography

External Resources

View on PubMed Access via DOI PubMed (31222786)

Popular Topics

Recent Journals