Development of a classification method for mild liver fibrosis using non-contrast CT image.
Ryo HiranoPatrik RogallaChristin FarrellBernice HoppelYasuko FujisawaShigeharu OhyuChihiro HattoriTakuya SakaguchiPublished in: International journal of computer assisted radiology and surgery (2022)
A new non-invasive and cost-effective method was developed to classify liver diseases between "non-fibrosis" (F0) and "fibrosis" (F1-F4). The proposed method makes it possible to detect liver fibrosis in asymptomatic patients using non-contrast CT images for better patient management and treatment.
Keyphrases
- liver fibrosis
- deep learning
- contrast enhanced
- magnetic resonance
- end stage renal disease
- computed tomography
- image quality
- ejection fraction
- newly diagnosed
- dual energy
- machine learning
- magnetic resonance imaging
- case report
- peritoneal dialysis
- convolutional neural network
- positron emission tomography
- patient reported outcomes
- smoking cessation
- patient reported