Ultrasound Image Classification Using ACGAN with Small Training Dataset

B-mode ultrasound imaging is a popular medical technique. Like other image processing tasks, deep learning has been used for analysis of images in the last few years. However, training models require large labeled datasets, which often unavailable images. The lack data bottleneck use analysis. To overcome this challenge, work, we exploit auxiliary classifier generative adversarial network (ACGAN) that combines benefits augmentation and transfer same framework. We conduct experiment on dataset breast shows effectiveness proposed approach.