A Deep Learning Approach for Varicocele Detection from Ultrasound Images

Varicocele is a disease characterized by abnormal dilatation of the scrotal venous plexus pampiniformis. It is a common cause of infertility and may cause pain or discomfort in some cases. In this article, we present a new approach for automatic classification of varicocele using Deep Learning convolutional neural networks. The available dataset consists of images converted to different color modes. Each color mode dataset is partitioned, augmented, and trained using a Deep Learning network. Experiments were conducted with all possible combinations of four different pre-trained models and over three color modes to determine the best combination that achieves the highest performance, with and without augmentation. Training and testing were evaluated using various metrics. Analysis of the results demonstrated the effectiveness of the proposed system. Results showed an accuracy of 83.1% with the RGB color mode when using ResNet50, and that the effect of augmentation was small.