Fig. 4
From: Improving lesion detection in mammograms by leveraging a Cycle-GAN-based lesion remover
Explantion of lesion detectors. This figure illustrates how we train lesion detectors using the original and lesion highlighted lesions. We used four different deep network architectures including ResNet18, DenseNet201, EfficientNetV2, and Vision Transformer (ViT) as our lesion detector. For each detector, we built Baseline model using original patch, Highlighted model using highlighted patch, and Combined by combining the scores from Baseline and Highlighted using logistic regression