Artificial intelligence-based, semi-automated segmentation for the extraction of ultrasound-derived radiomics features in breast cancer: a prospective multicenter study.

Abstract

Authors

• Tommaso Vincenzo Bartolotta
  Department of Radiology, Fondazione Istituto G. Giglio, Ct.da Pietrapollastra, Cefalù, Palermo, Italy.
• Carmelo Militello
  Institute for High-Performance Computing and Networking (ICAR-CNR), Italian National Research Council, Palermo, Italy.
• Francesco Prinzi
  Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), University of Palermo, Palermo, Italy.
• Fabiola Ferraro
  Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), University of Palermo, Palermo, Italy.
• Leonardo Rundo
  Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK; Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0RE, UK. Electronic address: lr495@cam.ac.uk.
• Calogero Zarcaro
  Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), University of Palermo, Palermo, Italy.
• Mariangela Dimarco
  Breast Unit, Fondazione Istituto "G. Giglio", Cefalù, PA, Italy.
• Alessia Angela Maria Orlando
  Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), University of Palermo, Palermo, Italy.
• Domenica Matranga
  Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties (ProMISE), University of Palermo, Palermo, Italy.
• Salvatore Vitabile
  Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), University of Palermo, Palermo, Italy. salvatore.vitabile@unipa.it.

Keywords

External Resources