Congress:
ECR24
Poster Number:
C-21633
Type:
EPOS Radiologist (scientific)
DOI:
10.26044/ecr2024/C-21633
Authorblock:
C. Salvatore1, M. Interlenghi1, E. Schiavon1, A. Lad1, D. Fazzini1, M. Alì1, S. Papa1, F. Sardanelli2, I. Castiglioni3; 1Milan/IT, 2San Donato Milanese, Milan/IT, 3Milano/IT
Disclosures:
Christian Salvatore:
Shareholder: DeepTrace Technologies S.R.L., Milan, Italy CEO: DeepTrace Technologies S.R.L., Milan, Italy
Matteo Interlenghi:
Shareholder: DeepTrace Technologies S.R.L., Milan, Italy Employee: DeepTrace Technologies S.R.L., Milan, Italy
Elia Schiavon:
Employee: DeepTrace Technologies S.R.L., Milan, Italy
Akash Lad:
Nothing to disclose
Deborah Fazzini:
Nothing to disclose
Marco Alì:
Other: Bracco Imaging
Sergio Papa:
Nothing to disclose
Francesco Sardanelli:
Nothing to disclose
Isabella Castiglioni:
Shareholder: DeepTrace Technologies S.R.L., Milan, Italy
Keywords:
Breast, Mammography, Computer Applications-General, Cancer
The purpose of this work was to assess the real-world performance of a deep learning algorithm integrated with a PACS and a mammography unit-vendor neutral system, for the automatic classification of breast density into 4 categories, according to the ACR BI-RADS.