Reducing the number of unnecessary biopsies for mammographic BI-RADS 4 lesions through a deep transfer learning method

Reducing the number of unnecessary biopsies for mammographic BI-RADS 4 lesions through a deep transfer learning method

Abstract Background In clinical practice, reducing unnecessary biopsies for mammographic BI-RADS 4 lesions is crucial. The objective of this study was to explore the potential value of deep transfer learning (DTL) based on the different fine-tuning strategies for Inception V3 to reduce the number of...

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Bibliographic Details
Main Authors: Mingzhu Meng, Hong Li, Ming Zhang, Guangyuan He, Long Wang, Dong Shen
Format: Article
Language:English
Published: BMC 2023-06-01
Series:BMC Medical Imaging
Subjects:
Residents
Deep transfer learning
Fine-tuning
Mammography
Breast lesions
Online Access:https://doi.org/10.1186/s12880-023-01023-4

Internet

https://doi.org/10.1186/s12880-023-01023-4

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