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S-Detect characterization of focal breast lesions according to the US BI RADS lexicon: a pictorial essay.

Tommaso Vincenzo BartolottaAlessia Angela Maria OrlandoLuigi SpataforaMariangela DimarcoCesare GagliardoAdele Taibbi
Published in: Journal of ultrasound (2020)
High-resolution ultrasonography (US) is a valuable tool in breast imaging. Nevertheless, US is an operator-dependent technique: to overcome this issue, the American College of Radiology (ACR) has developed the breast imaging-reporting and data system (BI-RADS) US lexicon. Despite this effort, the variability in the assessment of focal breast lesions (FBLs) with the use of BI-RADS US lexicon is still an issue. Within this framework, evidence shows that computer-aided image analysis may be effective in improving the radiologist's assessment of FBLs. In particular, S-Detect is a newly developed image-analytic computer program that provides assistance in morphologic analysis of FBLs seen on US according to the BI-RADS US lexicon. This pictorial essay describes state-of-the-art of sonographic characterization of FBLs by using S-Detect.
Keyphrases
  • high resolution
  • deep learning
  • mass spectrometry
  • artificial intelligence
  • emergency department
  • quality improvement
  • computed tomography
  • machine learning
  • contrast enhanced
  • adverse drug