Authors
Ehsan Kozegar, Mohsen Soryani, Hamid Behnam, Masoumeh Salamati, Tao Tan
Publication date
2020/3
Journal
Artificial Intelligence Review
Volume
53
Issue
3
Pages
1919-1941
Publisher
Springer Netherlands
Description
Nowadays, breast cancer is the leading cause of cancer death for women all over the world. Since the reason of breast cancer is unknown, early detection of the disease plays an important role in cancer control, saving lives and reducing costs. Among different modalities, automated 3-D breast ultrasound (3-D ABUS) is a new and effective imaging modality which has attracted a lot of interest as an adjunct to mammography for women with dense breasts. However, reading ABUS images is time consuming for radiologists and subtle abnormalities may be overlooked. Hence, computer aided detection (CADe) systems can be utilized as a second interpreter to assist radiologists to increase their screening speed and sensitivity. In this paper, a general architecture representing different CADe systems for ABUS images is introduced and the approaches for implementation of each block are categorized and …
Total citations
2020202120222023202451113157
Scholar articles
E Kozegar, M Soryani, H Behnam, M Salamati, T Tan - Artificial Intelligence Review, 2020