DBNet: a dual-branch network for breast cancer classification in ultrasound images

Hui Meng; Qingfeng Li; Xuefeng Liu; Yong Wang; Jianwei Niu

doi:10.1117/12.2608535

4 April 2022 DBNet: a dual-branch network for breast cancer classification in ultrasound images

Hui Meng, Qingfeng Li, Xuefeng Liu, Yong Wang, Jianwei Niu

Proceedings Volume 12033, Medical Imaging 2022: Computer-Aided Diagnosis; 120331U (2022) https://doi.org/10.1117/12.2608535
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Conference Poster

Abstract

Computer-aided diagnosis has been widely used in breast ultrasound images, and many deep learning-based models have emerged. However, the datasets used for breast ultrasound classification face the problem of category imbalance, which limits the accuracy of breast cancer classification. In this work, we propose a novel dual-branch network (DBNet) to alleviate the imbalance problem and improve classification accuracy. DBNet is constructed by conventional learning branch and re-balancing branch in parallel, which take universal sampling data and reversed sampling data as inputs, respectively. Both branches adopt ResNet-18 to extract features and share all the weights except for the last residual block. Additionally, both branches use the same classifier and share all the weights. The cross-entropy loss of each branch is calculated using the output logits and the corresponding groundtruth labels. The total loss of DBNet is designed as a linear weighted sum of two branches’ losses. To evaluate the performance of the DBNet, we conduct breast cancer classification on the dataset composed of 6309 ultrasound images with malignant nodules and 3527 ultrasound images with benign nodules. Furthermore, ResNet-18 and bilateral-branch network (BBN) are utilized as baselines. The results demonstrate that DBNet yields a result of 0.854 in accuracy, which outperforms the ResNet-18 and the BBN by 2.7% and 1.1%, respectively.

Citation Download Citation

Hui Meng, Qingfeng Li, Xuefeng Liu, Yong Wang, and Jianwei Niu "DBNet: a dual-branch network for breast cancer classification in ultrasound images", Proc. SPIE 12033, Medical Imaging 2022: Computer-Aided Diagnosis, 120331U (4 April 2022); https://doi.org/10.1117/12.2608535

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