Classification of Breast Lesions on DCE-MRI Data Using a Fine-Tuned MobileNet

被引：5
|
作者：
Wang, Long [1 ]
Zhang, Ming [1 ]
He, Guangyuan [1 ]
Shen, Dong [1 ]
Meng, Mingzhu [1 ]
机构：
[1] Nanjing Med Univ, Affiliated Changzhou Peoples Hosp 2, Dept Radiol, Changzhou 213164, Peoples R China
来源：
DIAGNOSTICS | 2023年 / 13卷 / 06期
关键词：
mobile convolutional neural networks; deep learning; breast lesions; magnetic resonance imaging; CANCER; DIAGNOSIS; MACHINE; MODEL;
D O I：
10.3390/diagnostics13061067
中图分类号：
R5 [内科学];
学科分类号：
1002 ; 100201 ;
摘要：
It is crucial to diagnose breast cancer early and accurately to optimize treatment. Presently, most deep learning models used for breast cancer detection cannot be used on mobile phones or low-power devices. This study intended to evaluate the capabilities of MobileNetV1 and MobileNetV2 and their fine-tuned models to differentiate malignant lesions from benign lesions in breast dynamic contrast-enhanced magnetic resonance images (DCE-MRI).
引用
收藏
页数：13
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