Detection and quantification of breast arterial calcifications on mammograms: a deep learning approach.

Journal: European radiology
Published Date: May 9, 2023

Abstract

OBJECTIVE: Breast arterial calcifications (BAC) are a sex-specific cardiovascular disease biomarker that might improve cardiovascular risk stratification in women. We implemented a deep convolutional neural network for automatic BAC detection and quantification.

Authors

  • Nazanin Mobini
    Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milan, Italy.
  • Marina Codari
    1 Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Morandi 30, San Donato Milanese, 20097 Milan, Italy.
  • Francesca Riva
    Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy.
  • Maria Giovanna Ienco
    Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy.
  • Davide Capra
    Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milan, Italy. davide.capra@unimi.it.
  • Andrea Cozzi
    Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133 Milano, Italy. Electronic address: andrea.cozzi1@unimi.it.
  • Serena Carriero
    Postgraduate School in Radiodiagnostics, Università degli Studi di Milano, Milan, Italy.
  • Diana Spinelli
    Postgraduation School in Radiodiagnostics, Università degli Studi di Milano, Milan, Italy.
  • Rubina Manuela Trimboli
    2 Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milan, Italy.
  • Giuseppe Baselli
  • Francesco Sardanelli
    1 Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Morandi 30, San Donato Milanese, 20097 Milan, Italy.

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