Convolutional neural network classification of ultrasound parametric images based on echo-envelope statistics for the quantitative diagnosis of liver steatosis
The formation of parametric images derived from the ES and the CNN classification of the parametric images were proposed for the quantitative diagnosis of liver steatosis. In more than 60% of the cases, the fatty liver grade could be estimated solely using ultrasound images.
Authors
- Kenji Yoshida (ORCID: https://orcid.org/0000-0002-2072-4351)
- Takayuki Kondo (ORCID: https://orcid.org/0000-0002-1075-9876)
- Shinnosuke Hirata (ORCID: https://orcid.org/0000-0001-6940-3287)
- Tadashi Yamaguchi (ORCID: https://orcid.org/0000-0001-5761-4888)
- Kisako Fujiwara
- A Isshiki
Institutions
- Chiba University (JP)
- Chiba University Hospital (JP)
Publication Details
- Journal
- Journal of Medical Ultrasonics
- Published
- 2024-11-23
- DOI
- https://doi.org/10.1007/s10396-024-01509-w
- Citations
- 2
- Primary Topic
- Liver Disease Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.77
Funders
- Takahashi Industrial and Economic Research Foundation
- Chiba University
- Japan Society for the Promotion of Science