Multi-Channel Input Deep Convolutional Neural Network for Mammogram Diagnosis
2020 International SoC Design Conference (ISOCC)(2020)
摘要
Medical image diagnosis should consider the information contained in multiple images, not just a single image, such as natural image classification. Mammography is the most basic X-ray screening method for diagnosing breast cancer, and mammograms have four images per patient. Convolutional neural networks should be able to diagnose using these four images. This paper proposes a convolutional neural network to simultaneously concatenate four images to solve the multi-view problem. The proposed network was trained and validated with the digital database for screening mammography (DDSM) and achieved 0.952 area under the ROC curve (AUC) for the two-class problem (positive vs. negative). This paper also proposes a new approach to localize lesions without patch labels or mask labels.
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关键词
Deep learning,Mammogram,Mammography,Multi-view classification
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