Deep Vision for Breast Cancer Classification and Segmentation

Deep Vision for Breast Cancer Classification and Segmentation

(1) Background: Female breast cancer diagnoses odds have increased from 11:1 in 1975 to 8:1 today. Mammography false positive rates (FPR) are associated with overdiagnoses and overtreatment, while false negative rates (FNR) increase morbidity and mortality. (2) Methods: Deep vision supervised learni...

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Bibliographic Details
Main Authors: Lawrence Fulton, Alex McLeod, Diane Dolezel, Nathaniel Bastian, Christopher P. Fulton
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Cancers
Subjects:
deep vision
breast cancer
machine learning
region of interest detection
Online Access:https://www.mdpi.com/2072-6694/13/21/5384

Internet

https://www.mdpi.com/2072-6694/13/21/5384

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