Automatic detection of breast masses using deep learning with YOLO approach-Reference-Cited by-同舟云学术

Automatic detection of breast masses using deep learning with YOLO approach

Published:2023-10-16 Issue:6 Volume:13 Page:915-923
ISSN:2190-7188
Container-title:Health and Technology
language:en
Short-container-title:Health Technol.

Author:

Quiñones-Espín Alejandro Ernesto^ORCID,Perez-Diaz Marlen^ORCID,Espín-Coto Rafaela Mayelín^ORCID,Rodriguez-Linares Deijany^ORCID,Lopez-Cabrera José Daniel^ORCID

Funder

Public Health Agency of Canada

Agency for Nuclear Energy and Advanced Technology of Cuba

Publisher

Springer Science and Business Media LLC

Subject

Biomedical Engineering,Applied Microbiology and Biotechnology,Bioengineering,Biotechnology

Link

https://link.springer.com/content/pdf/10.1007/s12553-023-00783-x.pdf

Reference26 articles.

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3. Mordang JJ, A. Gubern-Mérida A, Bria F, Tortorella G, Karssemeijer N. Improving computer-aided detection assistance in breast cancer screening by removal of obviously false-positive findings. Med Phys 2017;44:1390–1401.

4. Vilavedra GC, Ximenos BD, Cajal AG, Gómez EP, Gutiérrez SP. Densidad mamaria. Valoración e implicaciones en el manejo diagnóstico de la patología mamaria. Radiología 2018; 60. Proceeding of SERAM 2018, Elsevier, Spain.

5. Boumaraf S, Liu X, Ferkous C, Ma X. A New Computer-Aided Diagnosis System with Modified Genetic Feature Selection for BI-RADS Classification of Breast Masses in Mammograms. BioMed Res Int. 2020. https://doi.org/10.1155/2020/7695207.