A Novel Multistage Transfer Learning for Ultrasound Breast Cancer Image Classification.

ABSTRACT: Breast cancer diagnosis is one of the many areas that has taken advantage of artificial intelligence to achieve better performance, despite the fact that the availability of a large medical image dataset remains a challenge. Transfer learning (TL) is a phenomenon that enables deep learning algorithms to overcome the issue of shortage of training data in constructing an efficient model by transferring knowledge from a given source task to a target task. However, in most cases, ImageNet (natural images) pre-trained models that do not include medical images, are utilized for transfer learning to medical images. Considering the utilization of microscopic cancer cell line images that can be acquired in large amount, we argue that learning from both natural and medical datasets improves performa

SUBMITTER: Ayana G 

PROVIDER: S-EPMC8775102 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature