Predicting malignancy in breast lesions: enhancing accuracy with fine-tuned convolutional neural network models.

Journal: BMC medical imaging
Published Date: Nov 11, 2024

Abstract

BACKGROUND: This study aims to explore the accuracy of Convolutional Neural Network (CNN) models in predicting malignancy in Dynamic Contrast-Enhanced Breast Magnetic Resonance Imaging (DCE-BMRI).

Authors

  • Li Li
    Department of Gastric Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China.
  • Changjie Pan
    Radiology Department, the Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou 213164, Jiangsu, China.
  • Ming Zhang
    Heilongjiang Key Laboratory for Laboratory Animals and Comparative Medicine, College of Veterinary Medicine, Harbin 150030, China.
  • Dong Shen
    College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.
  • Guangyuan He
  • Mingzhu Meng
    Department of Radiology, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, China.

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