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).
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047403 | PMC |
| http://dx.doi.org/10.3390/diagnostics13061067 | DOI Listing |
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