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- Title
Artificial Intelligence-Based Breast Nodule Segmentation Using Multi-Scale Images and Convolutional Network.
- Authors
Quoc Tuan Hoang; Xuan Hien Pham; Anh Vu Le; Trung Thanh Bui
- Abstract
Diagnosing breast diseases using ultrasound (US) images remains challenging because it is time-consuming and requires expert radiologist knowledge. As a result, the diagnostic performance is significantly biased. To assist radiologists in this process, computer-aided diagnosis (CAD) systems have been developed and used in practice. This type of system is used not only to assist radiologists in examining breast ultrasound images (BUS) but also to ensure the effectiveness of the diagnostic process. In this study, we propose a new approach for breast lesion localization and segmentation using a multi-scale pyramid of the ultrasound image of a breast organ and a convolutional semantic segmentation network. Unlike previous studies that used only a deep detection/segmentation neural network on a single breast ultrasound image, we propose to use multiple images generated from an input image at different scales for the localization and segmentation process. By combining the localization/segmentation results obtained from the input image at different scales, the system performance was enhanced compared with that of the previous studies. The experimental results with two public datasets confirmed the effectiveness of the proposed approach by producing superior localization/segmentation results compared with those obtained in previous studies.
- Subjects
ARTIFICIAL intelligence; COMPUTER-aided diagnosis; BREAST ultrasound; ULTRASONIC imaging; BREAST; BREAST imaging
- Publication
KSII Transactions on Internet & Information Systems, 2023, Vol 17, Issue 3, p678
- ISSN
1976-7277
- Publication type
Article
- DOI
10.3837/tiis.2023.03.001