Discrimination of benign and malignant breast lesions on dynamic contrast-enhanced magnetic resonance imaging using deep learning.

Journal: Journal of cancer research and therapeutics

Published Date: Dec 28, 2023

Abstract

PURPOSE: To evaluate the capability of deep transfer learning (DTL) and fine-tuning methods in differentiating malignant from benign lesions in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

Authors

Ming Zhang

Heilongjiang Key Laboratory for Laboratory Animals and Comparative Medicine, College of Veterinary Medicine, Harbin 150030, China.
Guangyuan He
Changjie Pan

Radiology Department, the Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou 213164, Jiangsu, China.
Bing Yun

Teaching and Research Department of English, Nanjing Forestry University Nanjing 210037, Jiangsu Province, P.R. China.
Dong Shen

College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.
Mingzhu Meng

Department of Radiology, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, China.

Keywords

Breast Breast Neoplasms Contrast Media Deep Learning Diagnosis, Differential Diffusion Magnetic Resonance Imaging Female Humans Magnetic Resonance Imaging Retrospective Studies ROC Curve Sensitivity and Specificity

External Resources

View on PubMed Access via DOI PubMed (38156926)

Discrimination of benign and malignant breast lesions on dynamic contrast-enhanced magnetic resonance imaging using deep learning.

Abstract

Authors

Keywords

External Resources

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