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

页数：13

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