Interpretable machine learning for characterization of focal liver lesions by contrast-enhanced ultrasound

HIGHLIGHTS

• who: Contrast-Enhanced Ultrasound and collaborators from the was granted by Research Compliance Office, Stanford University and CA , USA have published the research: Interpretable Machine Learning for Characterization of Focal Liver Lesions by Contrast-Enhanced Ultrasound, in the Journal: (JOURNAL) of February/16,/2022
• what: - This work proposes an interpretable radiomics approach to differentiate between malignant and benign focal liver lesions (FLLs) on (CEUS). To fully exploit the wealth of information in CEUS while coping with these challenges here the authors propose combining features extracted by the temporal and spatiotemporal analysis in the arterial phase . . .
  

   

  

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